tmin-preProcess.R
ana
Tue Oct 10 14:04:13 2017
El objetivo de este documento es probar una red bayesiana para realizar predicción sobre los datos de sensores. Para ello aprendemos una red bayesiana y ajustamos sus parámetros, considerando los datos de entrada como continuos (no realizamos discretización), por eso veremos que se samplean la distribución de cada nodo/variable a una gaussiana. El dataset utilizado es de valores diarios de cuatro estaciones meteorologicas del DACC. Las variables diarias son: temperatura (máxima, minima y media), y humedad (maxima, minima y media)
5/10/2017 PROBAR ESTE CODIGO Y TAMBIEN GENERACION HTML ### Preprocesando el dataset
source("bnlearn-utils.R")##
## Attaching package: 'bnlearn'## The following object is masked from 'package:stats':
##
## sigmaset.seed(147)
library(readr)
sensores <- read_csv("~/phd-repos/tmin/bnlearn/data/sensores.csv")## Warning: Missing column names filled in: 'X1' [1]## Parsed with column specification:
## cols(
## .default = col_double(),
## X1 = col_datetime(format = "")
## )## See spec(...) for full column specifications.Variables del dataset
colnames(sensores)## [1] "X1" "S10.max" "S11.max"
## [4] "S12.max" "S13.max" "S14.max"
## [7] "S15.max" "S16.max" "S17.max"
## [10] "S18.max" "S19.max" "S1.max"
## [13] "S20.max" "S2.max" "S3.max"
## [16] "S4.max" "S5.max" "S6.max"
## [19] "S7.max" "S8.max" "S9.max"
## [22] "S10.media" "S11.media" "S12.media"
## [25] "S13.media" "S14.media" "S15.media"
## [28] "S16.media" "S17.media" "S18.media"
## [31] "S19.media" "S1.media" "S20.media"
## [34] "S2.media" "S3.media" "S4.media"
## [37] "S5.media" "S6.media" "S7.media"
## [40] "S8.media" "S9.media" "S10.min"
## [43] "S11.min" "S12.min" "S13.min"
## [46] "S14.min" "S15.min" "S16.min"
## [49] "S17.min" "S18.min" "S19.min"
## [52] "S1.min" "S20.min" "S2.min"
## [55] "S3.min" "S4.min" "S5.min"
## [58] "S6.min" "S7.min" "S8.min"
## [61] "S9.min" "S10.15hs" "S11.15hs"
## [64] "S12.15hs" "S13.15hs" "S14.15hs"
## [67] "S15.15hs" "S16.15hs" "S17.15hs"
## [70] "S18.15hs" "S19.15hs" "S1.15hs"
## [73] "S20.15hs" "S2.15hs" "S3.15hs"
## [76] "S4.15hs" "S5.15hs" "S6.15hs"
## [79] "S7.15hs" "S8.15hs" "S9.15hs"
## [82] "S10.12hs" "S11.12hs" "S12.12hs"
## [85] "S13.12hs" "S14.12hs" "S15.12hs"
## [88] "S16.12hs" "S17.12hs" "S18.12hs"
## [91] "S19.12hs" "S1.12hs" "S20.12hs"
## [94] "S2.12hs" "S3.12hs" "S4.12hs"
## [97] "S5.12hs" "S6.12hs" "S7.12hs"
## [100] "S8.12hs" "S9.12hs" "S10.18hs"
## [103] "S11.18hs" "S12.18hs" "S13.18hs"
## [106] "S14.18hs" "S15.18hs" "S16.18hs"
## [109] "S17.18hs" "S18.18hs" "S19.18hs"
## [112] "S1.18hs" "S20.18hs" "S2.18hs"
## [115] "S3.18hs" "S4.18hs" "S5.18hs"
## [118] "S6.18hs" "S7.18hs" "S8.18hs"
## [121] "S9.18hs" "Est.humedad_min" "Est.humedad_med"
## [124] "Est.humedad_max" "Est.temp_min" "Est.temp_max"
## [127] "Est.temp_med"Una vista breve
head(sensores)## # A tibble: 6 x 127
## X1 S10.max S11.max S12.max S13.max S14.max S15.max
## <dttm> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2013-09-07 23:00:41 31.0 30.0 32.0 31.5 32.0 31.0
## 2 2013-09-08 23:00:41 30.5 29.5 31.5 30.5 31.0 30.0
## 3 2013-09-09 23:00:41 34.0 32.5 34.0 34.0 34.0 33.5
## 4 2013-09-10 23:00:41 35.5 35.0 36.0 36.0 35.5 35.0
## 5 2013-09-11 23:00:41 24.5 24.0 24.5 24.5 24.0 24.5
## 6 2013-09-12 23:00:41 10.5 10.0 11.0 11.0 11.0 10.5
## # ... with 120 more variables: S16.max <dbl>, S17.max <dbl>,
## # S18.max <dbl>, S19.max <dbl>, S1.max <dbl>, S20.max <dbl>,
## # S2.max <dbl>, S3.max <dbl>, S4.max <dbl>, S5.max <dbl>, S6.max <dbl>,
## # S7.max <dbl>, S8.max <dbl>, S9.max <dbl>, S10.media <dbl>,
## # S11.media <dbl>, S12.media <dbl>, S13.media <dbl>, S14.media <dbl>,
## # S15.media <dbl>, S16.media <dbl>, S17.media <dbl>, S18.media <dbl>,
## # S19.media <dbl>, S1.media <dbl>, S20.media <dbl>, S2.media <dbl>,
## # S3.media <dbl>, S4.media <dbl>, S5.media <dbl>, S6.media <dbl>,
## # S7.media <dbl>, S8.media <dbl>, S9.media <dbl>, S10.min <dbl>,
## # S11.min <dbl>, S12.min <dbl>, S13.min <dbl>, S14.min <dbl>,
## # S15.min <dbl>, S16.min <dbl>, S17.min <dbl>, S18.min <dbl>,
## # S19.min <dbl>, S1.min <dbl>, S20.min <dbl>, S2.min <dbl>,
## # S3.min <dbl>, S4.min <dbl>, S5.min <dbl>, S6.min <dbl>, S7.min <dbl>,
## # S8.min <dbl>, S9.min <dbl>, S10.15hs <dbl>, S11.15hs <dbl>,
## # S12.15hs <dbl>, S13.15hs <dbl>, S14.15hs <dbl>, S15.15hs <dbl>,
## # S16.15hs <dbl>, S17.15hs <dbl>, S18.15hs <dbl>, S19.15hs <dbl>,
## # S1.15hs <dbl>, S20.15hs <dbl>, S2.15hs <dbl>, S3.15hs <dbl>,
## # S4.15hs <dbl>, S5.15hs <dbl>, S6.15hs <dbl>, S7.15hs <dbl>,
## # S8.15hs <dbl>, S9.15hs <dbl>, S10.12hs <dbl>, S11.12hs <dbl>,
## # S12.12hs <dbl>, S13.12hs <dbl>, S14.12hs <dbl>, S15.12hs <dbl>,
## # S16.12hs <dbl>, S17.12hs <dbl>, S18.12hs <dbl>, S19.12hs <dbl>,
## # S1.12hs <dbl>, S20.12hs <dbl>, S2.12hs <dbl>, S3.12hs <dbl>,
## # S4.12hs <dbl>, S5.12hs <dbl>, S6.12hs <dbl>, S7.12hs <dbl>,
## # S8.12hs <dbl>, S9.12hs <dbl>, S10.18hs <dbl>, S11.18hs <dbl>,
## # S12.18hs <dbl>, S13.18hs <dbl>, S14.18hs <dbl>, S15.18hs <dbl>, ...Cantidad de filas y columnas
cat("Rows: ",nrow(sensores)," Columns: ",ncol(sensores))## Rows: 465 Columns: 127como denomino a las variables que quiero predecir
pred_sensores = c("S10.min_t","S11.min_t","S12.min_t","S13.min_t","S14.min_t","S15.min_t","S16.min_t","S18.min_t", "S19.min_t","S1.min_t","S20.min_t","S2.min_t","S3.min_t","S4.min_t","S5.min_t",
"S6.min_t","S7.min_t","S8.min_t","S9.min_t")
pred_sensores## [1] "S10.min_t" "S11.min_t" "S12.min_t" "S13.min_t" "S14.min_t"
## [6] "S15.min_t" "S16.min_t" "S18.min_t" "S19.min_t" "S1.min_t"
## [11] "S20.min_t" "S2.min_t" "S3.min_t" "S4.min_t" "S5.min_t"
## [16] "S6.min_t" "S7.min_t" "S8.min_t" "S9.min_t"Columnas a borrar
erase <- colnames(sensores)[1]
erase## [1] "X1"sensores <- sensores[,-which(names(sensores) %in% erase)]
colnames(sensores)## [1] "S10.max" "S11.max" "S12.max"
## [4] "S13.max" "S14.max" "S15.max"
## [7] "S16.max" "S17.max" "S18.max"
## [10] "S19.max" "S1.max" "S20.max"
## [13] "S2.max" "S3.max" "S4.max"
## [16] "S5.max" "S6.max" "S7.max"
## [19] "S8.max" "S9.max" "S10.media"
## [22] "S11.media" "S12.media" "S13.media"
## [25] "S14.media" "S15.media" "S16.media"
## [28] "S17.media" "S18.media" "S19.media"
## [31] "S1.media" "S20.media" "S2.media"
## [34] "S3.media" "S4.media" "S5.media"
## [37] "S6.media" "S7.media" "S8.media"
## [40] "S9.media" "S10.min" "S11.min"
## [43] "S12.min" "S13.min" "S14.min"
## [46] "S15.min" "S16.min" "S17.min"
## [49] "S18.min" "S19.min" "S1.min"
## [52] "S20.min" "S2.min" "S3.min"
## [55] "S4.min" "S5.min" "S6.min"
## [58] "S7.min" "S8.min" "S9.min"
## [61] "S10.15hs" "S11.15hs" "S12.15hs"
## [64] "S13.15hs" "S14.15hs" "S15.15hs"
## [67] "S16.15hs" "S17.15hs" "S18.15hs"
## [70] "S19.15hs" "S1.15hs" "S20.15hs"
## [73] "S2.15hs" "S3.15hs" "S4.15hs"
## [76] "S5.15hs" "S6.15hs" "S7.15hs"
## [79] "S8.15hs" "S9.15hs" "S10.12hs"
## [82] "S11.12hs" "S12.12hs" "S13.12hs"
## [85] "S14.12hs" "S15.12hs" "S16.12hs"
## [88] "S17.12hs" "S18.12hs" "S19.12hs"
## [91] "S1.12hs" "S20.12hs" "S2.12hs"
## [94] "S3.12hs" "S4.12hs" "S5.12hs"
## [97] "S6.12hs" "S7.12hs" "S8.12hs"
## [100] "S9.12hs" "S10.18hs" "S11.18hs"
## [103] "S12.18hs" "S13.18hs" "S14.18hs"
## [106] "S15.18hs" "S16.18hs" "S17.18hs"
## [109] "S18.18hs" "S19.18hs" "S1.18hs"
## [112] "S20.18hs" "S2.18hs" "S3.18hs"
## [115] "S4.18hs" "S5.18hs" "S6.18hs"
## [118] "S7.18hs" "S8.18hs" "S9.18hs"
## [121] "Est.humedad_min" "Est.humedad_med" "Est.humedad_max"
## [124] "Est.temp_min" "Est.temp_max" "Est.temp_med"Procedemos a armar un dataset con las variables, colocando los datos de hace dos días, luego hace un día y luego día presente. Por ello, desfazamos el dataset para que queden primero las variables en T-2, T-1 y luego en t o tiempo presente.
sensores_T_2 <- sensores[1:(nrow(sensores)-2),]
sensores_T_1 <- sensores[2:(nrow(sensores)-1),] # no incluyo la primera fila
sensores_t <- sensores[3:nrow(sensores),] renombro las columnas
colnames(sensores_T_2) <- paste(colnames(sensores_T_2),"_T_2",sep="")
colnames(sensores_T_1) <- paste(colnames(sensores_T_1),"_T_1",sep="")
colnames(sensores_t) <- paste(colnames(sensores_t),"_t",sep="")del tiempo presente solo me interesa la temperatura mínima, las que quiero predecir
sensores_t <- sensores_t[,pred_sensores]creo dataset de datos de T-2, T-1 y t
df <- cbind.data.frame(sensores_T_2,sensores_T_1,sensores_t)nombres de las variables a usar para entrenar/testear
colnames(df)## [1] "S10.max_T_2" "S11.max_T_2" "S12.max_T_2"
## [4] "S13.max_T_2" "S14.max_T_2" "S15.max_T_2"
## [7] "S16.max_T_2" "S17.max_T_2" "S18.max_T_2"
## [10] "S19.max_T_2" "S1.max_T_2" "S20.max_T_2"
## [13] "S2.max_T_2" "S3.max_T_2" "S4.max_T_2"
## [16] "S5.max_T_2" "S6.max_T_2" "S7.max_T_2"
## [19] "S8.max_T_2" "S9.max_T_2" "S10.media_T_2"
## [22] "S11.media_T_2" "S12.media_T_2" "S13.media_T_2"
## [25] "S14.media_T_2" "S15.media_T_2" "S16.media_T_2"
## [28] "S17.media_T_2" "S18.media_T_2" "S19.media_T_2"
## [31] "S1.media_T_2" "S20.media_T_2" "S2.media_T_2"
## [34] "S3.media_T_2" "S4.media_T_2" "S5.media_T_2"
## [37] "S6.media_T_2" "S7.media_T_2" "S8.media_T_2"
## [40] "S9.media_T_2" "S10.min_T_2" "S11.min_T_2"
## [43] "S12.min_T_2" "S13.min_T_2" "S14.min_T_2"
## [46] "S15.min_T_2" "S16.min_T_2" "S17.min_T_2"
## [49] "S18.min_T_2" "S19.min_T_2" "S1.min_T_2"
## [52] "S20.min_T_2" "S2.min_T_2" "S3.min_T_2"
## [55] "S4.min_T_2" "S5.min_T_2" "S6.min_T_2"
## [58] "S7.min_T_2" "S8.min_T_2" "S9.min_T_2"
## [61] "S10.15hs_T_2" "S11.15hs_T_2" "S12.15hs_T_2"
## [64] "S13.15hs_T_2" "S14.15hs_T_2" "S15.15hs_T_2"
## [67] "S16.15hs_T_2" "S17.15hs_T_2" "S18.15hs_T_2"
## [70] "S19.15hs_T_2" "S1.15hs_T_2" "S20.15hs_T_2"
## [73] "S2.15hs_T_2" "S3.15hs_T_2" "S4.15hs_T_2"
## [76] "S5.15hs_T_2" "S6.15hs_T_2" "S7.15hs_T_2"
## [79] "S8.15hs_T_2" "S9.15hs_T_2" "S10.12hs_T_2"
## [82] "S11.12hs_T_2" "S12.12hs_T_2" "S13.12hs_T_2"
## [85] "S14.12hs_T_2" "S15.12hs_T_2" "S16.12hs_T_2"
## [88] "S17.12hs_T_2" "S18.12hs_T_2" "S19.12hs_T_2"
## [91] "S1.12hs_T_2" "S20.12hs_T_2" "S2.12hs_T_2"
## [94] "S3.12hs_T_2" "S4.12hs_T_2" "S5.12hs_T_2"
## [97] "S6.12hs_T_2" "S7.12hs_T_2" "S8.12hs_T_2"
## [100] "S9.12hs_T_2" "S10.18hs_T_2" "S11.18hs_T_2"
## [103] "S12.18hs_T_2" "S13.18hs_T_2" "S14.18hs_T_2"
## [106] "S15.18hs_T_2" "S16.18hs_T_2" "S17.18hs_T_2"
## [109] "S18.18hs_T_2" "S19.18hs_T_2" "S1.18hs_T_2"
## [112] "S20.18hs_T_2" "S2.18hs_T_2" "S3.18hs_T_2"
## [115] "S4.18hs_T_2" "S5.18hs_T_2" "S6.18hs_T_2"
## [118] "S7.18hs_T_2" "S8.18hs_T_2" "S9.18hs_T_2"
## [121] "Est.humedad_min_T_2" "Est.humedad_med_T_2" "Est.humedad_max_T_2"
## [124] "Est.temp_min_T_2" "Est.temp_max_T_2" "Est.temp_med_T_2"
## [127] "S10.max_T_1" "S11.max_T_1" "S12.max_T_1"
## [130] "S13.max_T_1" "S14.max_T_1" "S15.max_T_1"
## [133] "S16.max_T_1" "S17.max_T_1" "S18.max_T_1"
## [136] "S19.max_T_1" "S1.max_T_1" "S20.max_T_1"
## [139] "S2.max_T_1" "S3.max_T_1" "S4.max_T_1"
## [142] "S5.max_T_1" "S6.max_T_1" "S7.max_T_1"
## [145] "S8.max_T_1" "S9.max_T_1" "S10.media_T_1"
## [148] "S11.media_T_1" "S12.media_T_1" "S13.media_T_1"
## [151] "S14.media_T_1" "S15.media_T_1" "S16.media_T_1"
## [154] "S17.media_T_1" "S18.media_T_1" "S19.media_T_1"
## [157] "S1.media_T_1" "S20.media_T_1" "S2.media_T_1"
## [160] "S3.media_T_1" "S4.media_T_1" "S5.media_T_1"
## [163] "S6.media_T_1" "S7.media_T_1" "S8.media_T_1"
## [166] "S9.media_T_1" "S10.min_T_1" "S11.min_T_1"
## [169] "S12.min_T_1" "S13.min_T_1" "S14.min_T_1"
## [172] "S15.min_T_1" "S16.min_T_1" "S17.min_T_1"
## [175] "S18.min_T_1" "S19.min_T_1" "S1.min_T_1"
## [178] "S20.min_T_1" "S2.min_T_1" "S3.min_T_1"
## [181] "S4.min_T_1" "S5.min_T_1" "S6.min_T_1"
## [184] "S7.min_T_1" "S8.min_T_1" "S9.min_T_1"
## [187] "S10.15hs_T_1" "S11.15hs_T_1" "S12.15hs_T_1"
## [190] "S13.15hs_T_1" "S14.15hs_T_1" "S15.15hs_T_1"
## [193] "S16.15hs_T_1" "S17.15hs_T_1" "S18.15hs_T_1"
## [196] "S19.15hs_T_1" "S1.15hs_T_1" "S20.15hs_T_1"
## [199] "S2.15hs_T_1" "S3.15hs_T_1" "S4.15hs_T_1"
## [202] "S5.15hs_T_1" "S6.15hs_T_1" "S7.15hs_T_1"
## [205] "S8.15hs_T_1" "S9.15hs_T_1" "S10.12hs_T_1"
## [208] "S11.12hs_T_1" "S12.12hs_T_1" "S13.12hs_T_1"
## [211] "S14.12hs_T_1" "S15.12hs_T_1" "S16.12hs_T_1"
## [214] "S17.12hs_T_1" "S18.12hs_T_1" "S19.12hs_T_1"
## [217] "S1.12hs_T_1" "S20.12hs_T_1" "S2.12hs_T_1"
## [220] "S3.12hs_T_1" "S4.12hs_T_1" "S5.12hs_T_1"
## [223] "S6.12hs_T_1" "S7.12hs_T_1" "S8.12hs_T_1"
## [226] "S9.12hs_T_1" "S10.18hs_T_1" "S11.18hs_T_1"
## [229] "S12.18hs_T_1" "S13.18hs_T_1" "S14.18hs_T_1"
## [232] "S15.18hs_T_1" "S16.18hs_T_1" "S17.18hs_T_1"
## [235] "S18.18hs_T_1" "S19.18hs_T_1" "S1.18hs_T_1"
## [238] "S20.18hs_T_1" "S2.18hs_T_1" "S3.18hs_T_1"
## [241] "S4.18hs_T_1" "S5.18hs_T_1" "S6.18hs_T_1"
## [244] "S7.18hs_T_1" "S8.18hs_T_1" "S9.18hs_T_1"
## [247] "Est.humedad_min_T_1" "Est.humedad_med_T_1" "Est.humedad_max_T_1"
## [250] "Est.temp_min_T_1" "Est.temp_max_T_1" "Est.temp_med_T_1"
## [253] "S10.min_t" "S11.min_t" "S12.min_t"
## [256] "S13.min_t" "S14.min_t" "S15.min_t"
## [259] "S16.min_t" "S18.min_t" "S19.min_t"
## [262] "S1.min_t" "S20.min_t" "S2.min_t"
## [265] "S3.min_t" "S4.min_t" "S5.min_t"
## [268] "S6.min_t" "S7.min_t" "S8.min_t"
## [271] "S9.min_t"nro de ejemplos
nrow(df)## [1] 463nro de variables
ncol(df)## [1] 271black list de aristas
bl <- get_blacklist(pred_sensores)## 'data.frame': 0 obs. of 2 variables:
## $ from: atomic
## ..- attr(*, "levels")= chr "S10.min_t" "S11.min_t" "S12.min_t" "S13.min_t" ...
## $ to : atomic
## ..- attr(*, "levels")= chr "S10.min_t" "S11.min_t" "S12.min_t" "S13.min_t" ...white list de aristas, lista de arcos que si o si tienen que ir en la red Bayesiana. Consideramos arcos dirigidos desde las variables _T_1 y _T_2 hacia el t de un mismo sensor
wl <- get_whitelist(pred_sensores,colnames(df),dataset_tmin_chaar = TRUE)## 'data.frame': 0 obs. of 2 variables:
## $ from: chr
## $ to : chrTraining set y test dataset
bl
df[,1:ncol(df)] <- lapply(df[,1:ncol(df)],as.numeric) # <- convertir a numeric
until <- round(nrow(df)*.67)
training.set = df[1:until, ] # This is training set to learn the parameters
test.set = df[until:nrow(df), ]
until## [1] 310Librería para aprendizaje de redes bayesianas
library(bnlearn) Aprendemos una red bayesiana usando el algoritmo hc y pasando como restricciones las white y black lists
start_time <- Sys.time()
print(start_time)## [1] "2017-10-10 14:04:14 ART"res = hc(training.set, whitelist=wl,blacklist = bl) # , cluster = cl) # no funciona esta funcion de cluster
end_time <- Sys.time()
print(end_time)## [1] "2017-10-10 14:14:30 ART"print(end_time - start_time)## Time difference of 10.27145 minsguardo modelo para más análisis o corridas posteriores
save(res, file = paste(file="hc-tminchaar-",Sys.time(),".RData",sep=""))Aprendizaje de parametros
start_time <- Sys.time()
fitted = bn.fit(res, training.set) # learning of parameters
end_time <- Sys.time()
end_time - start_time## Time difference of 0.1802835 secsMostramos los parámetros para los nodos que nos interesan predecir
fitted[pred_sensores]## $S10.min_t
##
## Parameters of node S10.min_t (Gaussian distribution)
##
## Conditional density: S10.min_t | S10.max_T_2 + S10.media_T_2 + S10.min_T_2 + S10.15hs_T_2 + S10.12hs_T_2 + S10.18hs_T_2 + Est.humedad_med_T_2 + Est.temp_min_T_2 + S10.max_T_1 + S10.media_T_1 + S3.media_T_1 + S10.min_T_1 + S10.15hs_T_1 + S10.12hs_T_1 + S10.18hs_T_1 + S20.18hs_T_1
## Coefficients:
## (Intercept) S10.max_T_2 S10.media_T_2
## -8.78843185 -0.05914428 -0.05708267
## S10.min_T_2 S10.15hs_T_2 S10.12hs_T_2
## -0.01668617 0.04360428 0.03888874
## S10.18hs_T_2 Est.humedad_med_T_2 Est.temp_min_T_2
## -0.12941890 0.03960874 0.23496228
## S10.max_T_1 S10.media_T_1 S3.media_T_1
## 0.27176614 -2.06185873 2.75452252
## S10.min_T_1 S10.15hs_T_1 S10.12hs_T_1
## 0.26484059 -0.40587919 0.06472412
## S10.18hs_T_1 S20.18hs_T_1
## 0.65504222 -0.54338786
## Standard deviation of the residuals: 2.268689
##
## $S11.min_t
##
## Parameters of node S11.min_t (Gaussian distribution)
##
## Conditional density: S11.min_t | S11.max_T_2 + S11.media_T_2 + S11.min_T_2 + S11.15hs_T_2 + S13.15hs_T_2 + S11.12hs_T_2 + S11.18hs_T_2 + S11.max_T_1 + S11.media_T_1 + S3.media_T_1 + S11.min_T_1 + S11.15hs_T_1 + S13.15hs_T_1 + S11.12hs_T_1 + S11.18hs_T_1 + S20.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S11.max_T_2 S11.media_T_2
## -7.43412313 -0.12833127 0.06246884
## S11.min_T_2 S11.15hs_T_2 S13.15hs_T_2
## -0.01897572 -0.82013902 0.77218176
## S11.12hs_T_2 S11.18hs_T_2 S11.max_T_1
## 0.04008697 -0.09732225 0.16551216
## S11.media_T_1 S3.media_T_1 S11.min_T_1
## -1.33276176 1.99074568 0.23188382
## S11.15hs_T_1 S13.15hs_T_1 S11.12hs_T_1
## 0.71055208 -0.93453458 0.07157966
## S11.18hs_T_1 S20.18hs_T_1 Est.humedad_min_T_1
## 0.76477594 -0.67648988 0.03993955
## Est.temp_min_T_1
## 0.21104407
## Standard deviation of the residuals: 2.219249
##
## $S12.min_t
##
## Parameters of node S12.min_t (Gaussian distribution)
##
## Conditional density: S12.min_t | S12.max_T_2 + S12.media_T_2 + S12.min_T_2 + S12.15hs_T_2 + S12.12hs_T_2 + S12.18hs_T_2 + S12.max_T_1 + S19.max_T_1 + S12.media_T_1 + S3.media_T_1 + S12.min_T_1 + S12.15hs_T_1 + S12.12hs_T_1 + S12.18hs_T_1 + S20.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S12.max_T_2 S12.media_T_2
## -7.97285437 -0.08439948 -0.11717722
## S12.min_T_2 S12.15hs_T_2 S12.12hs_T_2
## 0.03969820 0.13072209 -0.02700494
## S12.18hs_T_2 S12.max_T_1 S19.max_T_1
## -0.10748925 -0.02698793 0.28790182
## S12.media_T_1 S3.media_T_1 S12.min_T_1
## -1.75778243 2.39828130 0.26005303
## S12.15hs_T_1 S12.12hs_T_1 S12.18hs_T_1
## -0.33113989 0.06865269 0.57440751
## S20.18hs_T_1 Est.humedad_min_T_1 Est.temp_min_T_1
## -0.50410114 0.04389128 0.23528711
## Standard deviation of the residuals: 2.287008
##
## $S13.min_t
##
## Parameters of node S13.min_t (Gaussian distribution)
##
## Conditional density: S13.min_t | S13.max_T_2 + S13.media_T_2 + S13.min_T_2 + S13.15hs_T_2 + S13.12hs_T_2 + S13.18hs_T_2 + Est.temp_max_T_2 + S13.max_T_1 + S14.max_T_1 + S13.media_T_1 + S13.min_T_1 + S15.min_T_1 + S13.15hs_T_1 + S13.12hs_T_1 + S13.18hs_T_1 + S9.18hs_T_1 + Est.humedad_min_T_1
## Coefficients:
## (Intercept) S13.max_T_2 S13.media_T_2
## -7.004599667 -0.133019239 -0.121340829
## S13.min_T_2 S13.15hs_T_2 S13.12hs_T_2
## 0.024128181 0.158429165 -0.002191008
## S13.18hs_T_2 Est.temp_max_T_2 S13.max_T_1
## -0.023249787 0.181692717 -0.449458041
## S14.max_T_1 S13.media_T_1 S13.min_T_1
## 0.571577882 0.580923486 -1.190417586
## S15.min_T_1 S13.15hs_T_1 S13.12hs_T_1
## 1.468591518 -0.338069921 0.021674681
## S13.18hs_T_1 S9.18hs_T_1 Est.humedad_min_T_1
## 0.765901633 -0.508125080 0.045720366
## Standard deviation of the residuals: 2.192117
##
## $S14.min_t
##
## Parameters of node S14.min_t (Gaussian distribution)
##
## Conditional density: S14.min_t | S14.max_T_2 + S2.max_T_2 + S14.media_T_2 + S2.media_T_2 + S5.media_T_2 + S14.min_T_2 + S14.15hs_T_2 + S14.12hs_T_2 + S14.18hs_T_2 + S1.18hs_T_2 + S14.max_T_1 + S9.max_T_1 + S14.media_T_1 + S14.min_T_1 + S15.min_T_1 + S14.15hs_T_1 + S1.15hs_T_1 + S14.12hs_T_1 + S14.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S14.max_T_2 S2.max_T_2
## -7.55472153 0.48205893 -0.60430829
## S14.media_T_2 S2.media_T_2 S5.media_T_2
## -3.31451638 5.85279063 -2.49737010
## S14.min_T_2 S14.15hs_T_2 S14.12hs_T_2
## 0.05764324 0.10595919 -0.04266451
## S14.18hs_T_2 S1.18hs_T_2 S14.max_T_1
## 0.92523619 -1.01765878 0.89723017
## S9.max_T_1 S14.media_T_1 S14.min_T_1
## -0.74001679 0.45019038 -1.40032946
## S15.min_T_1 S14.15hs_T_1 S1.15hs_T_1
## 1.68989057 -0.89187011 0.73366925
## S14.12hs_T_1 S14.18hs_T_1 Est.humedad_min_T_1
## 0.06954540 0.09792288 0.04442722
## Est.temp_min_T_1
## 0.21520478
## Standard deviation of the residuals: 2.102336
##
## $S15.min_t
##
## Parameters of node S15.min_t (Gaussian distribution)
##
## Conditional density: S15.min_t | S15.max_T_2 + S10.media_T_2 + S15.media_T_2 + S15.min_T_2 + S15.15hs_T_2 + S15.12hs_T_2 + S15.18hs_T_2 + S14.max_T_1 + S15.max_T_1 + S15.media_T_1 + S6.media_T_1 + S14.min_T_1 + S15.min_T_1 + S15.15hs_T_1 + S15.12hs_T_1 + S15.18hs_T_1 + S20.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S15.max_T_2 S10.media_T_2
## -7.60915730 -0.16316802 -1.97765929
## S15.media_T_2 S15.min_T_2 S15.15hs_T_2
## 1.89902291 0.01334394 0.13288680
## S15.12hs_T_2 S15.18hs_T_2 S14.max_T_1
## 0.02212565 -0.06792121 0.62984656
## S15.max_T_1 S15.media_T_1 S6.media_T_1
## -0.42321996 -1.38162457 1.97586926
## S14.min_T_1 S15.min_T_1 S15.15hs_T_1
## -1.67835635 1.94262917 -0.41371043
## S15.12hs_T_1 S15.18hs_T_1 S20.18hs_T_1
## 0.05841978 0.73761537 -0.50137217
## Est.humedad_min_T_1 Est.temp_min_T_1
## 0.04381314 0.22721986
## Standard deviation of the residuals: 2.179504
##
## $S16.min_t
##
## Parameters of node S16.min_t (Gaussian distribution)
##
## Conditional density: S16.min_t | S16.max_T_2 + S16.media_T_2 + S16.min_T_2 + S16.15hs_T_2 + S16.12hs_T_2 + S16.18hs_T_2 + S16.max_T_1 + S16.media_T_1 + S10.min_T_1 + S14.min_T_1 + S16.min_T_1 + S16.15hs_T_1 + S16.12hs_T_1 + S16.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S16.max_T_2 S16.media_T_2
## -6.46653131 -0.08711184 -0.08532295
## S16.min_T_2 S16.15hs_T_2 S16.12hs_T_2
## -0.01307393 0.11323413 -0.01480756
## S16.18hs_T_2 S16.max_T_1 S16.media_T_1
## -0.07660945 0.29321538 0.62807573
## S10.min_T_1 S14.min_T_1 S16.min_T_1
## 1.72837479 -1.17463014 -0.28311065
## S16.15hs_T_1 S16.12hs_T_1 S16.18hs_T_1
## -0.32901924 0.06234108 -0.00358083
## Est.humedad_min_T_1 Est.temp_min_T_1
## 0.03441361 0.20498351
## Standard deviation of the residuals: 2.334231
##
## $S18.min_t
##
## Parameters of node S18.min_t (Gaussian distribution)
##
## Conditional density: S18.min_t | S18.max_T_2 + S18.media_T_2 + S18.min_T_2 + S18.15hs_T_2 + S18.12hs_T_2 + S18.18hs_T_2 + Est.humedad_min_T_2 + Est.temp_min_T_2 + S18.max_T_1 + S18.media_T_1 + S18.min_T_1 + S18.15hs_T_1 + S18.12hs_T_1 + S18.18hs_T_1
## Coefficients:
## (Intercept) S18.max_T_2 S18.media_T_2
## -8.1391343975 0.0771427855 -0.1152253481
## S18.min_T_2 S18.15hs_T_2 S18.12hs_T_2
## -0.0078758712 -0.0409763233 0.0004090797
## S18.18hs_T_2 Est.humedad_min_T_2 Est.temp_min_T_2
## -0.0893631381 0.0421744747 0.2271073515
## S18.max_T_1 S18.media_T_1 S18.min_T_1
## 0.3462090726 0.5607180311 0.3138541126
## S18.15hs_T_1 S18.12hs_T_1 S18.18hs_T_1
## -0.3332917645 0.0451438572 0.0059703220
## Standard deviation of the residuals: 2.284291
##
## $S19.min_t
##
## Parameters of node S19.min_t (Gaussian distribution)
##
## Conditional density: S19.min_t | S19.max_T_2 + S19.media_T_2 + S19.min_T_2 + S19.15hs_T_2 + S19.12hs_T_2 + S19.18hs_T_2 + S19.max_T_1 + S19.media_T_1 + S10.min_T_1 + S19.min_T_1 + S19.15hs_T_1 + S19.12hs_T_1 + S19.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S19.max_T_2 S19.media_T_2
## -6.660490588 -0.090601677 -0.101697154
## S19.min_T_2 S19.15hs_T_2 S19.12hs_T_2
## -0.007468933 0.086181204 -0.037746150
## S19.18hs_T_2 S19.max_T_1 S19.media_T_1
## -0.050735141 0.389183568 0.592459821
## S10.min_T_1 S19.min_T_1 S19.15hs_T_1
## 1.047416973 -0.744984318 -0.372678114
## S19.12hs_T_1 S19.18hs_T_1 Est.humedad_min_T_1
## 0.133162792 -0.084951610 0.034533020
## Est.temp_min_T_1
## 0.216766231
## Standard deviation of the residuals: 2.309704
##
## $S1.min_t
##
## Parameters of node S1.min_t (Gaussian distribution)
##
## Conditional density: S1.min_t | S1.max_T_2 + S1.media_T_2 + S2.media_T_2 + S1.min_T_2 + S1.15hs_T_2 + S1.12hs_T_2 + S3.12hs_T_2 + S1.18hs_T_2 + S1.max_T_1 + S1.media_T_1 + S1.min_T_1 + S1.15hs_T_1 + S9.15hs_T_1 + S1.12hs_T_1 + S1.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S1.max_T_2 S1.media_T_2
## -7.14872308 -0.12119030 -2.75514577
## S2.media_T_2 S1.min_T_2 S1.15hs_T_2
## 2.82873388 0.02290666 0.11677842
## S1.12hs_T_2 S3.12hs_T_2 S1.18hs_T_2
## 0.45737788 -0.56049307 -0.11060086
## S1.max_T_1 S1.media_T_1 S1.min_T_1
## 0.11688082 0.43105004 0.33359335
## S1.15hs_T_1 S9.15hs_T_1 S1.12hs_T_1
## 0.65443296 -0.70803018 0.08354919
## S1.18hs_T_1 Est.humedad_min_T_1 Est.temp_min_T_1
## 0.01316498 0.04260006 0.23212011
## Standard deviation of the residuals: 2.281077
##
## $S20.min_t
##
## Parameters of node S20.min_t (Gaussian distribution)
##
## Conditional density: S20.min_t | S20.max_T_2 + S20.media_T_2 + S20.min_T_2 + S3.min_T_2 + S20.15hs_T_2 + S20.12hs_T_2 + S20.18hs_T_2 + Est.humedad_med_T_2 + Est.temp_min_T_2 + S20.max_T_1 + S20.media_T_1 + S3.media_T_1 + S20.min_T_1 + S20.15hs_T_1 + S20.12hs_T_1 + S20.18hs_T_1
## Coefficients:
## (Intercept) S20.max_T_2 S20.media_T_2
## -8.574134888 0.045838710 0.038844720
## S20.min_T_2 S3.min_T_2 S20.15hs_T_2
## 1.231110470 -1.333069360 -0.043224103
## S20.12hs_T_2 S20.18hs_T_2 Est.humedad_med_T_2
## -0.004716139 -0.126032945 0.041742490
## Est.temp_min_T_2 S20.max_T_1 S20.media_T_1
## 0.232966764 0.151583687 -1.670652758
## S3.media_T_1 S20.min_T_1 S20.15hs_T_1
## 2.410677469 0.267495150 -0.207677250
## S20.12hs_T_1 S20.18hs_T_1
## 0.051357136 -0.016658423
## Standard deviation of the residuals: 2.270306
##
## $S2.min_t
##
## Parameters of node S2.min_t (Gaussian distribution)
##
## Conditional density: S2.min_t | S2.max_T_2 + S2.media_T_2 + S2.min_T_2 + S2.15hs_T_2 + S2.12hs_T_2 + S2.18hs_T_2 + S2.max_T_1 + S2.media_T_1 + S9.media_T_1 + S2.min_T_1 + S2.15hs_T_1 + S2.12hs_T_1 + S15.18hs_T_1 + S2.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S2.max_T_2 S2.media_T_2
## -6.7597347708 -0.2029507101 0.0002423661
## S2.min_T_2 S2.15hs_T_2 S2.12hs_T_2
## -0.0090554911 0.1800304643 0.0051849238
## S2.18hs_T_2 S2.max_T_1 S2.media_T_1
## -0.1415906659 0.3707157839 2.9673879223
## S9.media_T_1 S2.min_T_1 S2.15hs_T_1
## -2.4656438080 0.3770423716 -0.4096330207
## S2.12hs_T_1 S15.18hs_T_1 S2.18hs_T_1
## 0.0394778027 0.5558072627 -0.4415176075
## Est.humedad_min_T_1 Est.temp_min_T_1
## 0.0403830855 0.2021750720
## Standard deviation of the residuals: 2.208427
##
## $S3.min_t
##
## Parameters of node S3.min_t (Gaussian distribution)
##
## Conditional density: S3.min_t | S3.max_T_2 + S10.media_T_2 + S3.media_T_2 + S3.min_T_2 + S4.min_T_2 + S3.15hs_T_2 + S2.12hs_T_2 + S3.12hs_T_2 + S3.18hs_T_2 + Est.humedad_min_T_2 + Est.temp_min_T_2 + S19.max_T_1 + S3.max_T_1 + S3.media_T_1 + S9.media_T_1 + S3.min_T_1 + S3.15hs_T_1 + S3.12hs_T_1 + S20.18hs_T_1 + S3.18hs_T_1
## Coefficients:
## (Intercept) S3.max_T_2 S10.media_T_2
## -6.19283800 -0.08297307 -2.14577008
## S3.media_T_2 S3.min_T_2 S4.min_T_2
## 2.07695744 -1.59904115 1.66346028
## S3.15hs_T_2 S2.12hs_T_2 S3.12hs_T_2
## 0.19978431 0.79192378 -0.85808111
## S3.18hs_T_2 Est.humedad_min_T_2 Est.temp_min_T_2
## -0.20093834 0.03687167 0.20057157
## S19.max_T_1 S3.max_T_1 S3.media_T_1
## 0.54991836 -0.42949260 2.16559247
## S9.media_T_1 S3.min_T_1 S3.15hs_T_1
## -1.62732280 0.31311347 -0.17268198
## S3.12hs_T_1 S20.18hs_T_1 S3.18hs_T_1
## 0.10264338 -0.85088853 0.88864949
## Standard deviation of the residuals: 2.097443
##
## $S4.min_t
##
## Parameters of node S4.min_t (Gaussian distribution)
##
## Conditional density: S4.min_t | S4.max_T_2 + S4.media_T_2 + S3.min_T_2 + S4.min_T_2 + S4.15hs_T_2 + S4.12hs_T_2 + S4.18hs_T_2 + Est.humedad_min_T_2 + Est.temp_min_T_2 + S4.max_T_1 + S4.media_T_1 + S9.media_T_1 + S4.min_T_1 + S1.15hs_T_1 + S4.15hs_T_1 + S4.12hs_T_1 + S4.18hs_T_1
## Coefficients:
## (Intercept) S4.max_T_2 S4.media_T_2
## -6.9389499231 -0.0532362823 -0.0939782854
## S3.min_T_2 S4.min_T_2 S4.15hs_T_2
## -1.3759281540 1.4001161280 0.1859803934
## S4.12hs_T_2 S4.18hs_T_2 Est.humedad_min_T_2
## -0.0332419765 -0.1467098400 0.0442681885
## Est.temp_min_T_2 S4.max_T_1 S4.media_T_1
## 0.2205455344 0.2651143268 2.1460619037
## S9.media_T_1 S4.min_T_1 S1.15hs_T_1
## -1.8620359624 0.4432661072 0.6315893262
## S4.15hs_T_1 S4.12hs_T_1 S4.18hs_T_1
## -0.7507025245 0.0249067013 0.0009362657
## Standard deviation of the residuals: 2.154875
##
## $S5.min_t
##
## Parameters of node S5.min_t (Gaussian distribution)
##
## Conditional density: S5.min_t | S5.max_T_2 + S2.media_T_2 + S5.media_T_2 + S5.min_T_2 + S5.15hs_T_2 + S5.12hs_T_2 + S5.18hs_T_2 + S5.max_T_1 + S5.media_T_1 + S5.min_T_1 + S5.15hs_T_1 + S5.12hs_T_1 + S20.18hs_T_1 + S5.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_max_T_1
## Coefficients:
## (Intercept) S5.max_T_2 S2.media_T_2
## -7.45434737 -0.07279115 2.89729143
## S5.media_T_2 S5.min_T_2 S5.15hs_T_2
## -2.92189541 0.07119363 0.05562918
## S5.12hs_T_2 S5.18hs_T_2 S5.max_T_1
## -0.01348697 -0.10389764 0.31407038
## S5.media_T_1 S5.min_T_1 S5.15hs_T_1
## 0.31760382 0.36340536 -0.31622552
## S5.12hs_T_1 S20.18hs_T_1 S5.18hs_T_1
## 0.07541302 -0.42404141 0.56314969
## Est.humedad_min_T_1 Est.temp_max_T_1
## 0.04219196 0.19781279
## Standard deviation of the residuals: 2.277346
##
## $S6.min_t
##
## Parameters of node S6.min_t (Gaussian distribution)
##
## Conditional density: S6.min_t | S6.max_T_2 + S6.media_T_2 + S6.min_T_2 + S6.15hs_T_2 + S6.12hs_T_2 + S6.18hs_T_2 + Est.temp_min_T_2 + S6.max_T_1 + S6.media_T_1 + S6.min_T_1 + S6.15hs_T_1 + S6.12hs_T_1 + S20.18hs_T_1 + S6.18hs_T_1 + Est.humedad_min_T_1
## Coefficients:
## (Intercept) S6.max_T_2 S6.media_T_2
## -7.42912622 -0.14869905 -0.07563388
## S6.min_T_2 S6.15hs_T_2 S6.12hs_T_2
## 0.00179470 0.13659265 0.01170648
## S6.18hs_T_2 Est.temp_min_T_2 S6.max_T_1
## -0.05975153 0.18065311 0.27818041
## S6.media_T_1 S6.min_T_1 S6.15hs_T_1
## 0.44934729 0.34860254 -0.31471713
## S6.12hs_T_1 S20.18hs_T_1 S6.18hs_T_1
## 0.04854650 -0.49218292 0.61871298
## Est.humedad_min_T_1
## 0.04075478
## Standard deviation of the residuals: 2.257891
##
## $S7.min_t
##
## Parameters of node S7.min_t (Gaussian distribution)
##
## Conditional density: S7.min_t | S7.max_T_2 + S7.media_T_2 + S7.min_T_2 + S7.15hs_T_2 + S7.12hs_T_2 + S7.18hs_T_2 + S7.max_T_1 + S7.media_T_1 + S9.media_T_1 + S7.min_T_1 + S7.15hs_T_1 + S7.12hs_T_1 + S6.18hs_T_1 + S7.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S7.max_T_2 S7.media_T_2
## -7.453560080 -0.162706520 -0.015482908
## S7.min_T_2 S7.15hs_T_2 S7.12hs_T_2
## -0.002451465 0.183817477 -0.047288964
## S7.18hs_T_2 S7.max_T_1 S7.media_T_1
## -0.105096069 0.250294993 2.189196003
## S9.media_T_1 S7.min_T_1 S7.15hs_T_1
## -1.830053649 0.363403517 -0.278620333
## S7.12hs_T_1 S6.18hs_T_1 S7.18hs_T_1
## 0.047008755 1.524192930 -1.347986215
## Est.humedad_min_T_1 Est.temp_min_T_1
## 0.036537280 0.212562928
## Standard deviation of the residuals: 2.300836
##
## $S8.min_t
##
## Parameters of node S8.min_t (Gaussian distribution)
##
## Conditional density: S8.min_t | S8.max_T_2 + S8.media_T_2 + S8.min_T_2 + S8.15hs_T_2 + S8.12hs_T_2 + S1.18hs_T_2 + S8.18hs_T_2 + S8.max_T_1 + S8.media_T_1 + S10.min_T_1 + S14.min_T_1 + S8.min_T_1 + S8.15hs_T_1 + S8.12hs_T_1 + S13.18hs_T_1 + S8.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S8.max_T_2 S8.media_T_2
## -8.1968535895 -0.1126582359 -0.0878315743
## S8.min_T_2 S8.15hs_T_2 S8.12hs_T_2
## -0.0018989650 0.1384878243 -0.0124096201
## S1.18hs_T_2 S8.18hs_T_2 S8.max_T_1
## -0.9564626734 0.8468011283 0.1914599450
## S8.media_T_1 S10.min_T_1 S14.min_T_1
## 0.7553639963 2.0190711718 -1.4253649749
## S8.min_T_1 S8.15hs_T_1 S8.12hs_T_1
## -0.3934136829 -0.2419287847 -0.0002855044
## S13.18hs_T_1 S8.18hs_T_1 Est.humedad_min_T_1
## 0.8288982857 -0.7643000593 0.0423988070
## Est.temp_min_T_1
## 0.2397302464
## Standard deviation of the residuals: 2.318468
##
## $S9.min_t
##
## Parameters of node S9.min_t (Gaussian distribution)
##
## Conditional density: S9.min_t | S9.max_T_2 + S9.media_T_2 + S9.min_T_2 + S9.15hs_T_2 + S9.12hs_T_2 + S9.18hs_T_2 + S14.max_T_1 + S9.max_T_1 + S4.media_T_1 + S9.media_T_1 + S9.min_T_1 + S9.15hs_T_1 + S9.12hs_T_1 + S6.18hs_T_1 + S9.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S9.max_T_2 S9.media_T_2
## -6.30495956 -0.17837268 -0.10304856
## S9.min_T_2 S9.15hs_T_2 S9.12hs_T_2
## 0.02066393 0.18410067 -0.01569690
## S9.18hs_T_2 S14.max_T_1 S9.max_T_1
## -0.08330836 0.63822130 -0.39156874
## S4.media_T_1 S9.media_T_1 S9.min_T_1
## 1.83564879 -1.41754445 0.37035429
## S9.15hs_T_1 S9.12hs_T_1 S6.18hs_T_1
## -0.30140188 0.06361516 0.64622635
## S9.18hs_T_1 Est.humedad_min_T_1 Est.temp_min_T_1
## -0.50068411 0.04077637 0.25580356
## Standard deviation of the residuals: 2.302476bn.fit.qqplot(fitted[[ncol(df)]])## Loading required namespace: lattice
bn.fit.xyplot(fitted[[ncol(df)]])
bn.fit.histogram(fitted[[ncol(df)]])
Markov blanket de las variables de interés para predecir
for(i in 1:length(pred_sensores))
{
cat("Markov blanket of ",pred_sensores[i],"\n")
print(mb(res,pred_sensores[i]))
}## Markov blanket of S10.min_t
## [1] "S10.max_T_2" "S10.media_T_2" "S10.min_T_2"
## [4] "S10.15hs_T_2" "S10.12hs_T_2" "S10.18hs_T_2"
## [7] "Est.humedad_med_T_2" "Est.temp_min_T_2" "S10.max_T_1"
## [10] "S10.media_T_1" "S3.media_T_1" "S10.min_T_1"
## [13] "S10.15hs_T_1" "S10.12hs_T_1" "S10.18hs_T_1"
## [16] "S20.18hs_T_1"
## Markov blanket of S11.min_t
## [1] "S11.max_T_2" "S11.media_T_2" "S13.media_T_2"
## [4] "S16.media_T_2" "S11.min_T_2" "S11.15hs_T_2"
## [7] "S13.15hs_T_2" "S11.12hs_T_2" "S11.18hs_T_2"
## [10] "S11.max_T_1" "S14.max_T_1" "S10.media_T_1"
## [13] "S11.media_T_1" "S15.media_T_1" "S3.media_T_1"
## [16] "S11.min_T_1" "S12.min_T_1" "S13.min_T_1"
## [19] "S15.min_T_1" "S2.min_T_1" "S11.15hs_T_1"
## [22] "S12.15hs_T_1" "S13.15hs_T_1" "S11.12hs_T_1"
## [25] "S11.18hs_T_1" "S20.18hs_T_1" "Est.humedad_min_T_1"
## [28] "Est.temp_min_T_1" "S2.min_t"
## Markov blanket of S12.min_t
## [1] "S12.max_T_2" "S12.media_T_2" "S12.min_T_2"
## [4] "S15.min_T_2" "S20.min_T_2" "S2.min_T_2"
## [7] "S3.min_T_2" "S4.min_T_2" "S8.min_T_2"
## [10] "S12.15hs_T_2" "S12.12hs_T_2" "S12.18hs_T_2"
## [13] "S12.max_T_1" "S19.max_T_1" "S12.media_T_1"
## [16] "S3.media_T_1" "S12.min_T_1" "S12.15hs_T_1"
## [19] "S12.12hs_T_1" "S12.18hs_T_1" "S20.18hs_T_1"
## [22] "Est.humedad_min_T_1" "Est.temp_min_T_1" "S13.min_t"
## Markov blanket of S13.min_t
## [1] "S13.max_T_2" "S13.media_T_2" "S13.min_T_2"
## [4] "S15.min_T_2" "S20.min_T_2" "S2.min_T_2"
## [7] "S3.min_T_2" "S4.min_T_2" "S8.min_T_2"
## [10] "S13.15hs_T_2" "S13.12hs_T_2" "S13.18hs_T_2"
## [13] "Est.temp_max_T_2" "S13.max_T_1" "S14.max_T_1"
## [16] "S13.media_T_1" "S13.min_T_1" "S15.min_T_1"
## [19] "S13.15hs_T_1" "S13.12hs_T_1" "S13.18hs_T_1"
## [22] "S9.18hs_T_1" "Est.humedad_min_T_1" "S12.min_t"
## Markov blanket of S14.min_t
## [1] "S14.max_T_2" "S2.max_T_2" "S14.media_T_2"
## [4] "S2.media_T_2" "S5.media_T_2" "S14.min_T_2"
## [7] "S14.15hs_T_2" "S14.12hs_T_2" "S14.18hs_T_2"
## [10] "S1.18hs_T_2" "S14.max_T_1" "S9.max_T_1"
## [13] "S14.media_T_1" "S14.min_T_1" "S15.min_T_1"
## [16] "S14.15hs_T_1" "S1.15hs_T_1" "S14.12hs_T_1"
## [19] "S14.18hs_T_1" "Est.humedad_min_T_1" "Est.temp_min_T_1"
## Markov blanket of S15.min_t
## [1] "S15.max_T_2" "S10.media_T_2" "S15.media_T_2"
## [4] "S15.min_T_2" "S3.min_T_2" "S9.min_T_2"
## [7] "S15.15hs_T_2" "S15.12hs_T_2" "S15.18hs_T_2"
## [10] "S16.18hs_T_2" "Est.humedad_min_T_2" "Est.temp_max_T_2"
## [13] "S14.max_T_1" "S15.max_T_1" "S15.media_T_1"
## [16] "S6.media_T_1" "S14.min_T_1" "S15.min_T_1"
## [19] "S15.15hs_T_1" "S15.12hs_T_1" "S15.18hs_T_1"
## [22] "S20.18hs_T_1" "Est.humedad_min_T_1" "Est.temp_min_T_1"
## Markov blanket of S16.min_t
## [1] "S16.max_T_2" "S16.media_T_2" "S16.min_T_2"
## [4] "S16.15hs_T_2" "S16.12hs_T_2" "S16.18hs_T_2"
## [7] "S16.max_T_1" "S16.media_T_1" "S10.min_T_1"
## [10] "S14.min_T_1" "S16.min_T_1" "S16.15hs_T_1"
## [13] "S16.12hs_T_1" "S16.18hs_T_1" "Est.humedad_min_T_1"
## [16] "Est.temp_min_T_1"
## Markov blanket of S18.min_t
## [1] "S18.max_T_2" "S18.media_T_2" "S18.min_T_2"
## [4] "S18.15hs_T_2" "S18.12hs_T_2" "S18.18hs_T_2"
## [7] "Est.humedad_min_T_2" "Est.temp_min_T_2" "S18.max_T_1"
## [10] "S18.media_T_1" "S18.min_T_1" "S18.15hs_T_1"
## [13] "S18.12hs_T_1" "S18.18hs_T_1"
## Markov blanket of S19.min_t
## [1] "S19.max_T_2" "S19.media_T_2" "S19.min_T_2"
## [4] "S19.15hs_T_2" "S19.12hs_T_2" "S19.18hs_T_2"
## [7] "S19.max_T_1" "S19.media_T_1" "S10.min_T_1"
## [10] "S19.min_T_1" "S19.15hs_T_1" "S19.12hs_T_1"
## [13] "S19.18hs_T_1" "Est.humedad_min_T_1" "Est.temp_min_T_1"
## Markov blanket of S1.min_t
## [1] "S1.max_T_2" "S1.media_T_2" "S2.media_T_2"
## [4] "S1.min_T_2" "S1.15hs_T_2" "S1.12hs_T_2"
## [7] "S3.12hs_T_2" "S1.18hs_T_2" "S1.max_T_1"
## [10] "S1.media_T_1" "S1.min_T_1" "S1.15hs_T_1"
## [13] "S9.15hs_T_1" "S1.12hs_T_1" "S1.18hs_T_1"
## [16] "Est.humedad_min_T_1" "Est.temp_min_T_1"
## Markov blanket of S20.min_t
## [1] "S20.max_T_2" "S20.media_T_2" "S20.min_T_2"
## [4] "S3.min_T_2" "S20.15hs_T_2" "S20.12hs_T_2"
## [7] "S20.18hs_T_2" "Est.humedad_med_T_2" "Est.temp_min_T_2"
## [10] "S20.max_T_1" "S20.media_T_1" "S3.media_T_1"
## [13] "S20.min_T_1" "S20.15hs_T_1" "S20.12hs_T_1"
## [16] "S20.18hs_T_1"
## Markov blanket of S2.min_t
## [1] "S2.max_T_2" "S13.media_T_2" "S16.media_T_2"
## [4] "S2.media_T_2" "S2.min_T_2" "S2.15hs_T_2"
## [7] "S2.12hs_T_2" "S2.18hs_T_2" "S14.max_T_1"
## [10] "S2.max_T_1" "S10.media_T_1" "S15.media_T_1"
## [13] "S2.media_T_1" "S9.media_T_1" "S11.min_T_1"
## [16] "S12.min_T_1" "S13.min_T_1" "S15.min_T_1"
## [19] "S2.min_T_1" "S12.15hs_T_1" "S2.15hs_T_1"
## [22] "S2.12hs_T_1" "S15.18hs_T_1" "S2.18hs_T_1"
## [25] "Est.humedad_min_T_1" "Est.temp_min_T_1" "S11.min_t"
## Markov blanket of S3.min_t
## [1] "S3.max_T_2" "S10.media_T_2" "S3.media_T_2"
## [4] "S3.min_T_2" "S4.min_T_2" "S3.15hs_T_2"
## [7] "S2.12hs_T_2" "S3.12hs_T_2" "S3.18hs_T_2"
## [10] "Est.humedad_min_T_2" "Est.temp_min_T_2" "S19.max_T_1"
## [13] "S3.max_T_1" "S3.media_T_1" "S9.media_T_1"
## [16] "S3.min_T_1" "S3.15hs_T_1" "S3.12hs_T_1"
## [19] "S20.18hs_T_1" "S3.18hs_T_1"
## Markov blanket of S4.min_t
## [1] "S4.max_T_2" "S4.media_T_2" "S3.min_T_2"
## [4] "S4.min_T_2" "S4.15hs_T_2" "S4.12hs_T_2"
## [7] "S4.18hs_T_2" "Est.humedad_min_T_2" "Est.temp_min_T_2"
## [10] "S4.max_T_1" "S4.media_T_1" "S9.media_T_1"
## [13] "S4.min_T_1" "S1.15hs_T_1" "S4.15hs_T_1"
## [16] "S4.12hs_T_1" "S4.18hs_T_1"
## Markov blanket of S5.min_t
## [1] "S5.max_T_2" "S2.media_T_2" "S5.media_T_2"
## [4] "S10.min_T_2" "S14.min_T_2" "S15.min_T_2"
## [7] "S3.min_T_2" "S5.min_T_2" "S7.min_T_2"
## [10] "S9.min_T_2" "S5.15hs_T_2" "S5.12hs_T_2"
## [13] "S5.18hs_T_2" "S5.max_T_1" "S5.media_T_1"
## [16] "S5.min_T_1" "S5.15hs_T_1" "S5.12hs_T_1"
## [19] "S20.18hs_T_1" "S5.18hs_T_1" "Est.humedad_min_T_1"
## [22] "Est.temp_max_T_1"
## Markov blanket of S6.min_t
## [1] "S6.max_T_2" "S6.media_T_2" "S6.min_T_2"
## [4] "S6.15hs_T_2" "S6.12hs_T_2" "S6.18hs_T_2"
## [7] "Est.temp_min_T_2" "S6.max_T_1" "S6.media_T_1"
## [10] "S6.min_T_1" "S6.15hs_T_1" "S6.12hs_T_1"
## [13] "S20.18hs_T_1" "S6.18hs_T_1" "Est.humedad_min_T_1"
## Markov blanket of S7.min_t
## [1] "S7.max_T_2" "S7.media_T_2" "S7.min_T_2"
## [4] "S7.15hs_T_2" "S7.12hs_T_2" "S7.18hs_T_2"
## [7] "Est.humedad_max_T_2" "S3.max_T_1" "S6.max_T_1"
## [10] "S7.max_T_1" "S10.media_T_1" "S13.media_T_1"
## [13] "S14.media_T_1" "S16.media_T_1" "S1.media_T_1"
## [16] "S2.media_T_1" "S3.media_T_1" "S6.media_T_1"
## [19] "S7.media_T_1" "S9.media_T_1" "S7.min_T_1"
## [22] "S15.15hs_T_1" "S2.15hs_T_1" "S3.15hs_T_1"
## [25] "S7.15hs_T_1" "S11.12hs_T_1" "S3.12hs_T_1"
## [28] "S6.12hs_T_1" "S7.12hs_T_1" "S9.12hs_T_1"
## [31] "S13.18hs_T_1" "S16.18hs_T_1" "S3.18hs_T_1"
## [34] "S4.18hs_T_1" "S6.18hs_T_1" "S7.18hs_T_1"
## [37] "S9.18hs_T_1" "Est.humedad_min_T_1" "Est.temp_min_T_1"
## Markov blanket of S8.min_t
## [1] "S8.max_T_2" "S8.media_T_2" "S8.min_T_2"
## [4] "S8.15hs_T_2" "S8.12hs_T_2" "S1.18hs_T_2"
## [7] "S8.18hs_T_2" "S8.max_T_1" "S8.media_T_1"
## [10] "S10.min_T_1" "S14.min_T_1" "S8.min_T_1"
## [13] "S8.15hs_T_1" "S8.12hs_T_1" "S13.18hs_T_1"
## [16] "S8.18hs_T_1" "Est.humedad_min_T_1" "Est.temp_min_T_1"
## Markov blanket of S9.min_t
## [1] "S9.max_T_2" "S9.media_T_2" "S9.min_T_2"
## [4] "S9.15hs_T_2" "S9.12hs_T_2" "S9.18hs_T_2"
## [7] "S14.max_T_1" "S9.max_T_1" "S4.media_T_1"
## [10] "S9.media_T_1" "S9.min_T_1" "S9.15hs_T_1"
## [13] "S9.12hs_T_1" "S6.18hs_T_1" "S9.18hs_T_1"
## [16] "Est.humedad_min_T_1" "Est.temp_min_T_1"Predicciones, evaluación en conjunto de testeo, caso regresión predicción temperaturas
df_res <- errors_regression(pred_sensores, fitted, test.set, verbose = FALSE)## Loading required package: zoo##
## Attaching package: 'zoo'## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric## Loading required package: timeDate## This is forecast 5.8## Testing on S10.min_t
## Testing on S11.min_t
## Testing on S12.min_t
## Testing on S13.min_t
## Testing on S14.min_t
## Testing on S15.min_t
## Testing on S16.min_t
## Testing on S18.min_t
## Testing on S19.min_t
## Testing on S1.min_t
## Testing on S20.min_t
## Testing on S2.min_t
## Testing on S3.min_t
## Testing on S4.min_t
## Testing on S5.min_t
## Testing on S6.min_t
## Testing on S7.min_t
## Testing on S8.min_t
## Testing on S9.min_tdf_res## Variable ME RMSE MAE
## 1 S10.min_t -0.362944641574646 2.2899332394924 1.77316329139593
## 2 S11.min_t -0.416125074462546 2.36656960229429 1.89525419938801
## 3 S12.min_t -0.475267489929335 2.2006144178408 1.73509872352605
## 4 S13.min_t -0.299453978698722 2.14396443628437 1.67179860274837
## 5 S14.min_t 0.418663232799487 2.36035461771123 1.92607133097722
## 6 S15.min_t -0.15724698144596 2.13060127209838 1.71180623764247
## 7 S16.min_t -0.282057148903732 2.43034719615218 1.94504789359944
## 8 S18.min_t -0.0465334298490033 2.17392240895557 1.70207623389368
## 9 S19.min_t -0.288405664909895 2.27764480885299 1.80973261965974
## 10 S1.min_t -0.506256678598324 2.30980631641046 1.79821263950664
## 11 S20.min_t -0.173931328655038 2.15736588899896 1.67591994226947
## 12 S2.min_t -0.121128968518394 2.14131305528717 1.70643833587752
## 13 S3.min_t -1.25094650330961 2.56099396957861 1.96383346691053
## 14 S4.min_t -0.273247724942762 2.27308263363553 1.77426008584375
## 15 S5.min_t 0.029926884430713 2.20492001278803 1.80400017052828
## 16 S6.min_t -0.274385426518909 2.10120885066763 1.65319596430228
## 17 S7.min_t -0.397589442829917 2.28991502725513 1.80925372281456
## 18 S8.min_t 0.264434487459849 2.46231067022081 1.92390064290928
## 19 S9.min_t -0.0827551124808375 2.34204243172663 1.83548890376768
## MPE MAPE
## 1 -Inf Inf
## 2 -Inf Inf
## 3 -Inf Inf
## 4 -Inf Inf
## 5 -Inf Inf
## 6 -7.95183434788504 65.1849683253801
## 7 NaN Inf
## 8 NaN Inf
## 9 NaN Inf
## 10 -Inf Inf
## 11 NaN Inf
## 12 -Inf Inf
## 13 -Inf Inf
## 14 -Inf Inf
## 15 -Inf Inf
## 16 -Inf Inf
## 17 -Inf Inf
## 18 NaN Inf
## 19 -Inf Infplots de R squared
r2_plots_inline(pred_sensores, fitted, test.set)
llamar confusionMatrix de caret, pasar primero “a factor of predicted classes, then a factor of classes to be used as the true results
breaks.binario <- c(-10,0,50) # caso Helada y no helada
my.breaks <- c(-10,-5,0,2,5,10,50)Caso binario: helada o no helada
conf_matrix_binario = conf_matrix(fitted,pred_sensores,test.set, breaks.binario)## Loading required package: lattice## Variable S10.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 12 3
## (0,50] 8 131
##
## Accuracy : 0.9286
## 95% CI : (0.8758, 0.9638)
## No Information Rate : 0.8701
## P-Value [Acc > NIR] : 0.01549
##
## Kappa : 0.6463
## Mcnemar's Test P-Value : 0.22780
##
## Sensitivity : 0.60000
## Specificity : 0.97761
## Pos Pred Value : 0.80000
## Neg Pred Value : 0.94245
## Prevalence : 0.12987
## Detection Rate : 0.07792
## Detection Prevalence : 0.09740
## Balanced Accuracy : 0.78881
##
## 'Positive' Class : (-10,0]
##
## Variable S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 11 3
## (0,50] 8 132
##
## Accuracy : 0.9286
## 95% CI : (0.8758, 0.9638)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.02677
##
## Kappa : 0.6277
## Mcnemar's Test P-Value : 0.22780
##
## Sensitivity : 0.57895
## Specificity : 0.97778
## Pos Pred Value : 0.78571
## Neg Pred Value : 0.94286
## Prevalence : 0.12338
## Detection Rate : 0.07143
## Detection Prevalence : 0.09091
## Balanced Accuracy : 0.77836
##
## 'Positive' Class : (-10,0]
##
## Variable S12.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 8 0
## (0,50] 11 135
##
## Accuracy : 0.9286
## 95% CI : (0.8758, 0.9638)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.026774
##
## Kappa : 0.5605
## Mcnemar's Test P-Value : 0.002569
##
## Sensitivity : 0.42105
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.92466
## Prevalence : 0.12338
## Detection Rate : 0.05195
## Detection Prevalence : 0.05195
## Balanced Accuracy : 0.71053
##
## 'Positive' Class : (-10,0]
##
## Variable S13.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 6 1
## (0,50] 13 134
##
## Accuracy : 0.9091
## 95% CI : (0.8522, 0.9494)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.133147
##
## Kappa : 0.4232
## Mcnemar's Test P-Value : 0.003283
##
## Sensitivity : 0.31579
## Specificity : 0.99259
## Pos Pred Value : 0.85714
## Neg Pred Value : 0.91156
## Prevalence : 0.12338
## Detection Rate : 0.03896
## Detection Prevalence : 0.04545
## Balanced Accuracy : 0.65419
##
## 'Positive' Class : (-10,0]
##
## Variable S14.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 10 1
## (0,50] 9 134
##
## Accuracy : 0.9351
## 95% CI : (0.8838, 0.9684)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.01333
##
## Kappa : 0.6335
## Mcnemar's Test P-Value : 0.02686
##
## Sensitivity : 0.52632
## Specificity : 0.99259
## Pos Pred Value : 0.90909
## Neg Pred Value : 0.93706
## Prevalence : 0.12338
## Detection Rate : 0.06494
## Detection Prevalence : 0.07143
## Balanced Accuracy : 0.75945
##
## 'Positive' Class : (-10,0]
##
## Variable S15.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 11 3
## (0,50] 8 132
##
## Accuracy : 0.9286
## 95% CI : (0.8758, 0.9638)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.02677
##
## Kappa : 0.6277
## Mcnemar's Test P-Value : 0.22780
##
## Sensitivity : 0.57895
## Specificity : 0.97778
## Pos Pred Value : 0.78571
## Neg Pred Value : 0.94286
## Prevalence : 0.12338
## Detection Rate : 0.07143
## Detection Prevalence : 0.09091
## Balanced Accuracy : 0.77836
##
## 'Positive' Class : (-10,0]
##
## Variable S16.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 7 0
## (0,50] 9 138
##
## Accuracy : 0.9416
## 95% CI : (0.892, 0.9729)
## No Information Rate : 0.8961
## P-Value [Acc > NIR] : 0.035620
##
## Kappa : 0.5823
## Mcnemar's Test P-Value : 0.007661
##
## Sensitivity : 0.43750
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.93878
## Prevalence : 0.10390
## Detection Rate : 0.04545
## Detection Prevalence : 0.04545
## Balanced Accuracy : 0.71875
##
## 'Positive' Class : (-10,0]
##
## Variable S18.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 11 1
## (0,50] 8 134
##
## Accuracy : 0.9416
## 95% CI : (0.892, 0.9729)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.006027
##
## Kappa : 0.679
## Mcnemar's Test P-Value : 0.045500
##
## Sensitivity : 0.57895
## Specificity : 0.99259
## Pos Pred Value : 0.91667
## Neg Pred Value : 0.94366
## Prevalence : 0.12338
## Detection Rate : 0.07143
## Detection Prevalence : 0.07792
## Balanced Accuracy : 0.78577
##
## 'Positive' Class : (-10,0]
##
## Variable S19.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 9 1
## (0,50] 10 134
##
## Accuracy : 0.9286
## 95% CI : (0.8758, 0.9638)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.02677
##
## Kappa : 0.5854
## Mcnemar's Test P-Value : 0.01586
##
## Sensitivity : 0.47368
## Specificity : 0.99259
## Pos Pred Value : 0.90000
## Neg Pred Value : 0.93056
## Prevalence : 0.12338
## Detection Rate : 0.05844
## Detection Prevalence : 0.06494
## Balanced Accuracy : 0.73314
##
## 'Positive' Class : (-10,0]
##
## Variable S1.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 8 0
## (0,50] 11 135
##
## Accuracy : 0.9286
## 95% CI : (0.8758, 0.9638)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.026774
##
## Kappa : 0.5605
## Mcnemar's Test P-Value : 0.002569
##
## Sensitivity : 0.42105
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.92466
## Prevalence : 0.12338
## Detection Rate : 0.05195
## Detection Prevalence : 0.05195
## Balanced Accuracy : 0.71053
##
## 'Positive' Class : (-10,0]
##
## Variable S20.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 13 3
## (0,50] 6 132
##
## Accuracy : 0.9416
## 95% CI : (0.892, 0.9729)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.006027
##
## Kappa : 0.7102
## Mcnemar's Test P-Value : 0.504985
##
## Sensitivity : 0.68421
## Specificity : 0.97778
## Pos Pred Value : 0.81250
## Neg Pred Value : 0.95652
## Prevalence : 0.12338
## Detection Rate : 0.08442
## Detection Prevalence : 0.10390
## Balanced Accuracy : 0.83099
##
## 'Positive' Class : (-10,0]
##
## Variable S2.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 6 0
## (0,50] 12 136
##
## Accuracy : 0.9221
## 95% CI : (0.8678, 0.9591)
## No Information Rate : 0.8831
## P-Value [Acc > NIR] : 0.078473
##
## Kappa : 0.469
## Mcnemar's Test P-Value : 0.001496
##
## Sensitivity : 0.33333
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.91892
## Prevalence : 0.11688
## Detection Rate : 0.03896
## Detection Prevalence : 0.03896
## Balanced Accuracy : 0.66667
##
## 'Positive' Class : (-10,0]
##
## Variable S3.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 5 2
## (0,50] 11 136
##
## Accuracy : 0.9156
## 95% CI : (0.86, 0.9543)
## No Information Rate : 0.8961
## P-Value [Acc > NIR] : 0.2611
##
## Kappa : 0.3966
## Mcnemar's Test P-Value : 0.0265
##
## Sensitivity : 0.31250
## Specificity : 0.98551
## Pos Pred Value : 0.71429
## Neg Pred Value : 0.92517
## Prevalence : 0.10390
## Detection Rate : 0.03247
## Detection Prevalence : 0.04545
## Balanced Accuracy : 0.64900
##
## 'Positive' Class : (-10,0]
##
## Variable S4.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 8 3
## (0,50] 10 133
##
## Accuracy : 0.9156
## 95% CI : (0.86, 0.9543)
## No Information Rate : 0.8831
## P-Value [Acc > NIR] : 0.12707
##
## Kappa : 0.5081
## Mcnemar's Test P-Value : 0.09609
##
## Sensitivity : 0.44444
## Specificity : 0.97794
## Pos Pred Value : 0.72727
## Neg Pred Value : 0.93007
## Prevalence : 0.11688
## Detection Rate : 0.05195
## Detection Prevalence : 0.07143
## Balanced Accuracy : 0.71119
##
## 'Positive' Class : (-10,0]
##
## Variable S5.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 8 0
## (0,50] 12 134
##
## Accuracy : 0.9221
## 95% CI : (0.8678, 0.9591)
## No Information Rate : 0.8701
## P-Value [Acc > NIR] : 0.030008
##
## Kappa : 0.5371
## Mcnemar's Test P-Value : 0.001496
##
## Sensitivity : 0.40000
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.91781
## Prevalence : 0.12987
## Detection Rate : 0.05195
## Detection Prevalence : 0.05195
## Balanced Accuracy : 0.70000
##
## 'Positive' Class : (-10,0]
##
## Variable S6.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 7 0
## (0,50] 10 137
##
## Accuracy : 0.9351
## 95% CI : (0.8838, 0.9684)
## No Information Rate : 0.8896
## P-Value [Acc > NIR] : 0.040278
##
## Kappa : 0.5547
## Mcnemar's Test P-Value : 0.004427
##
## Sensitivity : 0.41176
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.93197
## Prevalence : 0.11039
## Detection Rate : 0.04545
## Detection Prevalence : 0.04545
## Balanced Accuracy : 0.70588
##
## 'Positive' Class : (-10,0]
##
## Variable S7.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 10 2
## (0,50] 11 131
##
## Accuracy : 0.9156
## 95% CI : (0.86, 0.9543)
## No Information Rate : 0.8636
## P-Value [Acc > NIR] : 0.03322
##
## Kappa : 0.5627
## Mcnemar's Test P-Value : 0.02650
##
## Sensitivity : 0.47619
## Specificity : 0.98496
## Pos Pred Value : 0.83333
## Neg Pred Value : 0.92254
## Prevalence : 0.13636
## Detection Rate : 0.06494
## Detection Prevalence : 0.07792
## Balanced Accuracy : 0.73058
##
## 'Positive' Class : (-10,0]
##
## Variable S8.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 13 5
## (0,50] 6 130
##
## Accuracy : 0.9286
## 95% CI : (0.8758, 0.9638)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.02677
##
## Kappa : 0.6621
## Mcnemar's Test P-Value : 1.00000
##
## Sensitivity : 0.68421
## Specificity : 0.96296
## Pos Pred Value : 0.72222
## Neg Pred Value : 0.95588
## Prevalence : 0.12338
## Detection Rate : 0.08442
## Detection Prevalence : 0.11688
## Balanced Accuracy : 0.82359
##
## 'Positive' Class : (-10,0]
##
## Variable S9.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 10 3
## (0,50] 11 130
##
## Accuracy : 0.9091
## 95% CI : (0.8522, 0.9494)
## No Information Rate : 0.8636
## P-Value [Acc > NIR] : 0.05791
##
## Kappa : 0.5403
## Mcnemar's Test P-Value : 0.06137
##
## Sensitivity : 0.47619
## Specificity : 0.97744
## Pos Pred Value : 0.76923
## Neg Pred Value : 0.92199
## Prevalence : 0.13636
## Detection Rate : 0.06494
## Detection Prevalence : 0.08442
## Balanced Accuracy : 0.72682
##
## 'Positive' Class : (-10,0]
## Evaluación de predicción en rangos de temperaturas
conf_matrix_temp = conf_matrix(fitted,pred_sensores,test.set, my.breaks)## Variable S10.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 1 11 3 0 0 0
## (0,2] 0 6 4 4 0 0
## (2,5] 0 2 5 8 6 0
## (5,10] 0 0 3 4 32 5
## (10,50] 0 0 0 0 14 46
##
## Overall Statistics
##
## Accuracy : 0.6558
## 95% CI : (0.5751, 0.7304)
## No Information Rate : 0.3377
## P-Value [Acc > NIR] : 8.142e-16
##
## Kappa : 0.5346
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.57895 0.26667
## Specificity 1.000000 0.97037 0.92806
## Pos Pred Value NaN 0.73333 0.28571
## Neg Pred Value 0.993506 0.94245 0.92143
## Prevalence 0.006494 0.12338 0.09740
## Detection Rate 0.000000 0.07143 0.02597
## Detection Prevalence 0.000000 0.09740 0.09091
## Balanced Accuracy 0.500000 0.77466 0.59736
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.50000 0.6154 0.9020
## Specificity 0.90580 0.8824 0.8641
## Pos Pred Value 0.38095 0.7273 0.7667
## Neg Pred Value 0.93985 0.8182 0.9468
## Prevalence 0.10390 0.3377 0.3312
## Detection Rate 0.05195 0.2078 0.2987
## Detection Prevalence 0.13636 0.2857 0.3896
## Balanced Accuracy 0.70290 0.7489 0.8830
## Variable S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 11 3 0 0 0
## (0,2] 0 6 4 3 1 0
## (2,5] 0 2 6 7 6 0
## (5,10] 0 0 4 7 27 4
## (10,50] 0 0 0 0 16 47
##
## Overall Statistics
##
## Accuracy : 0.6234
## 95% CI : (0.5418, 0.7001)
## No Information Rate : 0.3312
## P-Value [Acc > NIR] : 1.164e-13
##
## Kappa : 0.4908
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.57895 0.23529
## Specificity 1 0.97778 0.92701
## Pos Pred Value NA 0.78571 0.28571
## Neg Pred Value NA 0.94286 0.90714
## Prevalence 0 0.12338 0.11039
## Detection Rate 0 0.07143 0.02597
## Detection Prevalence 0 0.09091 0.09091
## Balanced Accuracy NA 0.77836 0.58115
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.41176 0.5400 0.9216
## Specificity 0.89781 0.8558 0.8447
## Pos Pred Value 0.33333 0.6429 0.7460
## Neg Pred Value 0.92481 0.7946 0.9560
## Prevalence 0.11039 0.3247 0.3312
## Detection Rate 0.04545 0.1753 0.3052
## Detection Prevalence 0.13636 0.2727 0.4091
## Balanced Accuracy 0.65479 0.6979 0.8831
## Variable S12.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 8 0 0 0 0
## (0,2] 0 8 6 2 0 0
## (2,5] 0 3 6 7 3 0
## (5,10] 0 0 4 6 32 5
## (10,50] 0 0 0 0 15 49
##
## Overall Statistics
##
## Accuracy : 0.6623
## 95% CI : (0.5818, 0.7365)
## No Information Rate : 0.3506
## P-Value [Acc > NIR] : 3.655e-15
##
## Kappa : 0.5349
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.42105 0.37500
## Specificity 1 1.00000 0.92754
## Pos Pred Value NA 1.00000 0.37500
## Neg Pred Value NA 0.92466 0.92754
## Prevalence 0 0.12338 0.10390
## Detection Rate 0 0.05195 0.03896
## Detection Prevalence 0 0.05195 0.10390
## Balanced Accuracy NA 0.71053 0.65127
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.46667 0.6400 0.9074
## Specificity 0.91367 0.8558 0.8500
## Pos Pred Value 0.36842 0.6809 0.7656
## Neg Pred Value 0.94074 0.8318 0.9444
## Prevalence 0.09740 0.3247 0.3506
## Detection Rate 0.04545 0.2078 0.3182
## Detection Prevalence 0.12338 0.3052 0.4156
## Balanced Accuracy 0.69017 0.7479 0.8787
## Variable S13.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 6 0 1 0 0
## (0,2] 0 11 4 0 1 0
## (2,5] 0 2 6 7 5 0
## (5,10] 0 0 5 7 31 5
## (10,50] 0 0 0 0 10 53
##
## Overall Statistics
##
## Accuracy : 0.6558
## 95% CI : (0.5751, 0.7304)
## No Information Rate : 0.3766
## P-Value [Acc > NIR] : 2.159e-12
##
## Kappa : 0.5236
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.31579 0.26667
## Specificity 1 0.99259 0.91367
## Pos Pred Value NA 0.85714 0.25000
## Neg Pred Value NA 0.91156 0.92029
## Prevalence 0 0.12338 0.09740
## Detection Rate 0 0.03896 0.02597
## Detection Prevalence 0 0.04545 0.10390
## Balanced Accuracy NA 0.65419 0.59017
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.46667 0.6596 0.9138
## Specificity 0.90647 0.8411 0.8958
## Pos Pred Value 0.35000 0.6458 0.8413
## Neg Pred Value 0.94030 0.8491 0.9451
## Prevalence 0.09740 0.3052 0.3766
## Detection Rate 0.04545 0.2013 0.3442
## Detection Prevalence 0.12987 0.3117 0.4091
## Balanced Accuracy 0.68657 0.7503 0.9048
## Variable S14.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 10 1 0 0 0
## (0,2] 1 6 5 3 0 0
## (2,5] 0 2 5 11 8 0
## (5,10] 0 0 4 2 34 13
## (10,50] 0 0 0 0 8 41
##
## Overall Statistics
##
## Accuracy : 0.6558
## 95% CI : (0.5751, 0.7304)
## No Information Rate : 0.3506
## P-Value [Acc > NIR] : 1.317e-14
##
## Kappa : 0.5357
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.55556 0.33333
## Specificity 1.000000 0.99265 0.92806
## Pos Pred Value NaN 0.90909 0.33333
## Neg Pred Value 0.993506 0.94406 0.92806
## Prevalence 0.006494 0.11688 0.09740
## Detection Rate 0.000000 0.06494 0.03247
## Detection Prevalence 0.000000 0.07143 0.09740
## Balanced Accuracy 0.500000 0.77410 0.63070
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.68750 0.6800 0.7593
## Specificity 0.89130 0.8173 0.9200
## Pos Pred Value 0.42308 0.6415 0.8367
## Neg Pred Value 0.96094 0.8416 0.8762
## Prevalence 0.10390 0.3247 0.3506
## Detection Rate 0.07143 0.2208 0.2662
## Detection Prevalence 0.16883 0.3442 0.3182
## Balanced Accuracy 0.78940 0.7487 0.8396
## Variable S15.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 11 2 1 0 0
## (0,2] 0 6 4 3 0 0
## (2,5] 0 2 6 9 6 0
## (5,10] 0 0 4 6 33 8
## (10,50] 0 0 0 0 12 41
##
## Overall Statistics
##
## Accuracy : 0.6364
## 95% CI : (0.5551, 0.7123)
## No Information Rate : 0.3312
## P-Value [Acc > NIR] : 9.71e-15
##
## Kappa : 0.5102
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.57895 0.25000
## Specificity 1 0.97778 0.93478
## Pos Pred Value NA 0.78571 0.30769
## Neg Pred Value NA 0.94286 0.91489
## Prevalence 0 0.12338 0.10390
## Detection Rate 0 0.07143 0.02597
## Detection Prevalence 0 0.09091 0.08442
## Balanced Accuracy NA 0.77836 0.59239
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.47368 0.6471 0.8367
## Specificity 0.89630 0.8252 0.8857
## Pos Pred Value 0.39130 0.6471 0.7736
## Neg Pred Value 0.92366 0.8252 0.9208
## Prevalence 0.12338 0.3312 0.3182
## Detection Rate 0.05844 0.2143 0.2662
## Detection Prevalence 0.14935 0.3312 0.3442
## Balanced Accuracy 0.68499 0.7362 0.8612
## Variable S16.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 7 0 0 0 0
## (0,2] 0 7 5 6 0 0
## (2,5] 0 2 5 9 3 0
## (5,10] 0 0 3 5 27 7
## (10,50] 0 0 0 1 17 50
##
## Overall Statistics
##
## Accuracy : 0.6364
## 95% CI : (0.5551, 0.7123)
## No Information Rate : 0.3701
## P-Value [Acc > NIR] : 1.964e-11
##
## Kappa : 0.4963
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.43750 0.38462
## Specificity 1 1.00000 0.90780
## Pos Pred Value NA 1.00000 0.27778
## Neg Pred Value NA 0.93878 0.94118
## Prevalence 0 0.10390 0.08442
## Detection Rate 0 0.04545 0.03247
## Detection Prevalence 0 0.04545 0.11688
## Balanced Accuracy NA 0.71875 0.64621
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.42857 0.5745 0.8772
## Specificity 0.92481 0.8598 0.8144
## Pos Pred Value 0.47368 0.6429 0.7353
## Neg Pred Value 0.91111 0.8214 0.9186
## Prevalence 0.13636 0.3052 0.3701
## Detection Rate 0.05844 0.1753 0.3247
## Detection Prevalence 0.12338 0.2727 0.4416
## Balanced Accuracy 0.67669 0.7171 0.8458
## Variable S18.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 11 1 0 0 0
## (0,2] 0 7 6 2 0 0
## (2,5] 0 1 5 10 5 0
## (5,10] 0 0 4 4 33 6
## (10,50] 0 0 0 0 12 47
##
## Overall Statistics
##
## Accuracy : 0.6948
## 95% CI : (0.6156, 0.7664)
## No Information Rate : 0.3442
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.5849
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.57895 0.37500
## Specificity 1 0.99259 0.93478
## Pos Pred Value NA 0.91667 0.40000
## Neg Pred Value NA 0.94366 0.92806
## Prevalence 0 0.12338 0.10390
## Detection Rate 0 0.07143 0.03896
## Detection Prevalence 0 0.07792 0.09740
## Balanced Accuracy NA 0.78577 0.65489
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.62500 0.6600 0.8868
## Specificity 0.92029 0.8654 0.8812
## Pos Pred Value 0.47619 0.7021 0.7966
## Neg Pred Value 0.95489 0.8411 0.9368
## Prevalence 0.10390 0.3247 0.3442
## Detection Rate 0.06494 0.2143 0.3052
## Detection Prevalence 0.13636 0.3052 0.3831
## Balanced Accuracy 0.77264 0.7627 0.8840
## Variable S19.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 9 1 0 0 0
## (0,2] 0 8 5 3 0 0
## (2,5] 0 2 5 8 5 0
## (5,10] 0 0 4 5 32 4
## (10,50] 0 0 0 0 12 51
##
## Overall Statistics
##
## Accuracy : 0.6818
## 95% CI : (0.602, 0.7545)
## No Information Rate : 0.3571
## P-Value [Acc > NIR] : 2.788e-16
##
## Kappa : 0.5637
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.47368 0.33333
## Specificity 1 0.99259 0.92086
## Pos Pred Value NA 0.90000 0.31250
## Neg Pred Value NA 0.93056 0.92754
## Prevalence 0 0.12338 0.09740
## Detection Rate 0 0.05844 0.03247
## Detection Prevalence 0 0.06494 0.10390
## Balanced Accuracy NA 0.73314 0.62710
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.50000 0.6531 0.9273
## Specificity 0.91304 0.8762 0.8788
## Pos Pred Value 0.40000 0.7111 0.8095
## Neg Pred Value 0.94030 0.8440 0.9560
## Prevalence 0.10390 0.3182 0.3571
## Detection Rate 0.05195 0.2078 0.3312
## Detection Prevalence 0.12987 0.2922 0.4091
## Balanced Accuracy 0.70652 0.7646 0.9030
## Variable S1.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 8 0 0 0 0
## (0,2] 0 9 7 4 0 0
## (2,5] 0 2 5 8 3 0
## (5,10] 0 0 4 5 30 2
## (10,50] 0 0 0 0 14 53
##
## Overall Statistics
##
## Accuracy : 0.6883
## 95% CI : (0.6088, 0.7604)
## No Information Rate : 0.3571
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.5734
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.42105 0.43750
## Specificity 1 1.00000 0.90580
## Pos Pred Value NA 1.00000 0.35000
## Neg Pred Value NA 0.92466 0.93284
## Prevalence 0 0.12338 0.10390
## Detection Rate 0 0.05195 0.04545
## Detection Prevalence 0 0.05195 0.12987
## Balanced Accuracy NA 0.71053 0.67165
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.47059 0.6383 0.9636
## Specificity 0.92701 0.8972 0.8586
## Pos Pred Value 0.44444 0.7317 0.7910
## Neg Pred Value 0.93382 0.8496 0.9770
## Prevalence 0.11039 0.3052 0.3571
## Detection Rate 0.05195 0.1948 0.3442
## Detection Prevalence 0.11688 0.2662 0.4351
## Balanced Accuracy 0.69880 0.7677 0.9111
## Variable S20.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 1 12 3 0 0 0
## (0,2] 0 5 4 3 0 0
## (2,5] 0 1 4 9 8 0
## (5,10] 0 0 4 3 26 7
## (10,50] 0 0 0 0 13 51
##
## Overall Statistics
##
## Accuracy : 0.6623
## 95% CI : (0.5818, 0.7365)
## No Information Rate : 0.3766
## P-Value [Acc > NIR] : 6.693e-13
##
## Kappa : 0.5378
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.66667 0.26667
## Specificity 1.000000 0.97059 0.94245
## Pos Pred Value NaN 0.75000 0.33333
## Neg Pred Value 0.993506 0.95652 0.92254
## Prevalence 0.006494 0.11688 0.09740
## Detection Rate 0.000000 0.07792 0.02597
## Detection Prevalence 0.000000 0.10390 0.07792
## Balanced Accuracy 0.500000 0.81863 0.60456
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.60000 0.5532 0.8793
## Specificity 0.90647 0.8692 0.8646
## Pos Pred Value 0.40909 0.6500 0.7969
## Neg Pred Value 0.95455 0.8158 0.9222
## Prevalence 0.09740 0.3052 0.3766
## Detection Rate 0.05844 0.1688 0.3312
## Detection Prevalence 0.14286 0.2597 0.4156
## Balanced Accuracy 0.75324 0.7112 0.8719
## Variable S2.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 6 0 0 0 0
## (0,2] 0 10 4 4 1 0
## (2,5] 0 2 6 9 5 0
## (5,10] 0 0 4 6 31 7
## (10,50] 0 0 0 0 11 48
##
## Overall Statistics
##
## Accuracy : 0.6364
## 95% CI : (0.5551, 0.7123)
## No Information Rate : 0.3571
## P-Value [Acc > NIR] : 1.811e-12
##
## Kappa : 0.5037
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.33333 0.28571
## Specificity 1 1.00000 0.89286
## Pos Pred Value NA 1.00000 0.21053
## Neg Pred Value NA 0.91892 0.92593
## Prevalence 0 0.11688 0.09091
## Detection Rate 0 0.03896 0.02597
## Detection Prevalence 0 0.03896 0.12338
## Balanced Accuracy NA 0.66667 0.58929
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.47368 0.6458 0.8727
## Specificity 0.90370 0.8396 0.8889
## Pos Pred Value 0.40909 0.6458 0.8136
## Neg Pred Value 0.92424 0.8396 0.9263
## Prevalence 0.12338 0.3117 0.3571
## Detection Rate 0.05844 0.2013 0.3117
## Detection Prevalence 0.14286 0.3117 0.3831
## Balanced Accuracy 0.68869 0.7427 0.8808
## Variable S3.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 5 1 1 0 0
## (0,2] 0 7 6 1 0 0
## (2,5] 0 4 7 5 4 0
## (5,10] 0 0 5 9 18 4
## (10,50] 0 0 0 0 19 58
##
## Overall Statistics
##
## Accuracy : 0.5974
## 95% CI : (0.5154, 0.6755)
## No Information Rate : 0.4026
## P-Value [Acc > NIR] : 8.434e-07
##
## Kappa : 0.4306
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.31250 0.31579
## Specificity 1 0.98551 0.94074
## Pos Pred Value NA 0.71429 0.42857
## Neg Pred Value NA 0.92517 0.90714
## Prevalence 0 0.10390 0.12338
## Detection Rate 0 0.03247 0.03896
## Detection Prevalence 0 0.04545 0.09091
## Balanced Accuracy NA 0.64900 0.62827
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.31250 0.4390 0.9355
## Specificity 0.89130 0.8407 0.7935
## Pos Pred Value 0.25000 0.5000 0.7532
## Neg Pred Value 0.91791 0.8051 0.9481
## Prevalence 0.10390 0.2662 0.4026
## Detection Rate 0.03247 0.1169 0.3766
## Detection Prevalence 0.12987 0.2338 0.5000
## Balanced Accuracy 0.60190 0.6399 0.8645
## Variable S4.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 8 2 1 0 0
## (0,2] 0 8 8 2 0 0
## (2,5] 0 1 4 8 6 0
## (5,10] 0 1 4 6 27 7
## (10,50] 0 0 0 0 15 46
##
## Overall Statistics
##
## Accuracy : 0.6299
## 95% CI : (0.5484, 0.7062)
## No Information Rate : 0.3442
## P-Value [Acc > NIR] : 4.763e-13
##
## Kappa : 0.4978
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.44444 0.44444
## Specificity 1 0.97794 0.92647
## Pos Pred Value NA 0.72727 0.44444
## Neg Pred Value NA 0.93007 0.92647
## Prevalence 0 0.11688 0.11688
## Detection Rate 0 0.05195 0.05195
## Detection Prevalence 0 0.07143 0.11688
## Balanced Accuracy NA 0.71119 0.68546
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.47059 0.5625 0.8679
## Specificity 0.91971 0.8302 0.8515
## Pos Pred Value 0.42105 0.6000 0.7541
## Neg Pred Value 0.93333 0.8073 0.9247
## Prevalence 0.11039 0.3117 0.3442
## Detection Rate 0.05195 0.1753 0.2987
## Detection Prevalence 0.12338 0.2922 0.3961
## Balanced Accuracy 0.69515 0.6963 0.8597
## Variable S5.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 8 0 0 0 0
## (0,2] 1 8 6 3 1 0
## (2,5] 0 3 7 10 6 0
## (5,10] 0 0 2 2 32 7
## (10,50] 0 0 0 0 8 50
##
## Overall Statistics
##
## Accuracy : 0.6883
## 95% CI : (0.6088, 0.7604)
## No Information Rate : 0.3701
## P-Value [Acc > NIR] : 1.196e-15
##
## Kappa : 0.5791
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.42105 0.40000
## Specificity 1.000000 1.00000 0.90647
## Pos Pred Value NaN 1.00000 0.31579
## Neg Pred Value 0.993506 0.92466 0.93333
## Prevalence 0.006494 0.12338 0.09740
## Detection Rate 0.000000 0.05195 0.03896
## Detection Prevalence 0.000000 0.05195 0.12338
## Balanced Accuracy 0.500000 0.71053 0.65324
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.66667 0.6809 0.8772
## Specificity 0.88489 0.8972 0.9175
## Pos Pred Value 0.38462 0.7442 0.8621
## Neg Pred Value 0.96094 0.8649 0.9271
## Prevalence 0.09740 0.3052 0.3701
## Detection Rate 0.06494 0.2078 0.3247
## Detection Prevalence 0.16883 0.2792 0.3766
## Balanced Accuracy 0.77578 0.7890 0.8974
## Variable S6.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 7 0 0 0 0
## (0,2] 0 9 6 3 0 0
## (2,5] 0 1 4 9 6 0
## (5,10] 0 0 5 4 27 6
## (10,50] 0 0 0 0 10 57
##
## Overall Statistics
##
## Accuracy : 0.6883
## 95% CI : (0.6088, 0.7604)
## No Information Rate : 0.4091
## P-Value [Acc > NIR] : 2.408e-12
##
## Kappa : 0.5647
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.41176 0.40000
## Specificity 1 1.00000 0.91367
## Pos Pred Value NA 1.00000 0.33333
## Neg Pred Value NA 0.93197 0.93382
## Prevalence 0 0.11039 0.09740
## Detection Rate 0 0.04545 0.03896
## Detection Prevalence 0 0.04545 0.11688
## Balanced Accuracy NA 0.70588 0.65683
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.56250 0.6279 0.9048
## Specificity 0.92029 0.8649 0.8901
## Pos Pred Value 0.45000 0.6429 0.8507
## Neg Pred Value 0.94776 0.8571 0.9310
## Prevalence 0.10390 0.2792 0.4091
## Detection Rate 0.05844 0.1753 0.3701
## Detection Prevalence 0.12987 0.2727 0.4351
## Balanced Accuracy 0.74139 0.7464 0.8974
## Variable S7.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 10 2 0 0 0
## (0,2] 1 6 4 2 0 0
## (2,5] 0 4 5 8 5 0
## (5,10] 0 0 4 7 30 5
## (10,50] 0 0 0 0 13 48
##
## Overall Statistics
##
## Accuracy : 0.6494
## 95% CI : (0.5684, 0.7244)
## No Information Rate : 0.3442
## P-Value [Acc > NIR] : 1.204e-14
##
## Kappa : 0.5239
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.50000 0.26667
## Specificity 1.000000 0.98507 0.93525
## Pos Pred Value NaN 0.83333 0.30769
## Neg Pred Value 0.993506 0.92958 0.92199
## Prevalence 0.006494 0.12987 0.09740
## Detection Rate 0.000000 0.06494 0.02597
## Detection Prevalence 0.000000 0.07792 0.08442
## Balanced Accuracy 0.500000 0.74254 0.60096
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.47059 0.6250 0.9057
## Specificity 0.89781 0.8491 0.8713
## Pos Pred Value 0.36364 0.6522 0.7869
## Neg Pred Value 0.93182 0.8333 0.9462
## Prevalence 0.11039 0.3117 0.3442
## Detection Rate 0.05195 0.1948 0.3117
## Detection Prevalence 0.14286 0.2987 0.3961
## Balanced Accuracy 0.68420 0.7370 0.8885
## Variable S8.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 13 3 2 0 0
## (0,2] 0 4 6 3 0 0
## (2,5] 0 2 2 6 4 0
## (5,10] 0 0 4 5 34 9
## (10,50] 0 0 0 1 12 44
##
## Overall Statistics
##
## Accuracy : 0.6688
## 95% CI : (0.5885, 0.7425)
## No Information Rate : 0.3442
## P-Value [Acc > NIR] : 2.365e-16
##
## Kappa : 0.5465
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.68421 0.40000
## Specificity 1 0.96296 0.94964
## Pos Pred Value NA 0.72222 0.46154
## Neg Pred Value NA 0.95588 0.93617
## Prevalence 0 0.12338 0.09740
## Detection Rate 0 0.08442 0.03896
## Detection Prevalence 0 0.11688 0.08442
## Balanced Accuracy NA 0.82359 0.67482
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.35294 0.6800 0.8302
## Specificity 0.94161 0.8269 0.8713
## Pos Pred Value 0.42857 0.6538 0.7719
## Neg Pred Value 0.92143 0.8431 0.9072
## Prevalence 0.11039 0.3247 0.3442
## Detection Rate 0.03896 0.2208 0.2857
## Detection Prevalence 0.09091 0.3377 0.3701
## Balanced Accuracy 0.64727 0.7535 0.8507
## Variable S9.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 1 9 2 1 0 0
## (0,2] 1 6 5 1 1 0
## (2,5] 0 3 5 9 5 0
## (5,10] 0 1 3 6 33 6
## (10,50] 0 0 0 0 12 44
##
## Overall Statistics
##
## Accuracy : 0.6494
## 95% CI : (0.5684, 0.7244)
## No Information Rate : 0.3312
## P-Value [Acc > NIR] : 7.255e-16
##
## Kappa : 0.5271
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.00000 0.47368 0.33333
## Specificity 1.00000 0.97037 0.93525
## Pos Pred Value NaN 0.69231 0.35714
## Neg Pred Value 0.98701 0.92908 0.92857
## Prevalence 0.01299 0.12338 0.09740
## Detection Rate 0.00000 0.05844 0.03247
## Detection Prevalence 0.00000 0.08442 0.09091
## Balanced Accuracy 0.50000 0.72203 0.63429
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.52941 0.6471 0.8800
## Specificity 0.90511 0.8447 0.8846
## Pos Pred Value 0.40909 0.6735 0.7857
## Neg Pred Value 0.93939 0.8286 0.9388
## Prevalence 0.11039 0.3312 0.3247
## Detection Rate 0.05844 0.2143 0.2857
## Detection Prevalence 0.14286 0.3182 0.3636
## Balanced Accuracy 0.71726 0.7459 0.8823Test de predicción con randomForest
library(randomForest)## randomForest 4.6-12## Type rfNews() to see new features/changes/bug fixes.##
## Attaching package: 'randomForest'## The following object is masked from 'package:ggplot2':
##
## marginlibrary(miscTools)
library(ggplot2)
for(i in 1:length(pred_sensores))
{
# determinar la variable predictora
y_label <- pred_sensores[i]
df2 <- df
#' renombro variable predictora por y, para facilitar formula
colnames(df2)[which(colnames(df2)==y_label)] <- "y"
#' quito las otras variables predictoras, ya que solo analizaré la que se encuentre en y_label
#'
df2 <- df2[,-which(names(df2) %in% pred_sensores)]
colnames(df2)
# train y test set
until <- round(nrow(df2)*.67)
training.set = df2[1:until, ] # This is training set to learn the parameters
test.set = df2[until:nrow(df2), ]
model <- randomForest(y ~ ., data = training.set, importance = TRUE )
pred <- predict(model, test.set)
#View(cbind(pred,test.set$y))
mse <- mean((test.set$y - pred)^2)
r2 <- rSquared(test.set$y, test.set$y - pred)
cat("Variable ",pred_sensores[i]," MSE:",mse," Rsquared: ",r2)
#' Plot R_2, valores predichos vs valores reales
#'
p <- ggplot(aes(x=actual, y=pred),
data=data.frame(actual=test.set$y, pred=pred))
p2 <- p + geom_point() +
geom_abline(color="red") +
ggtitle(paste("RandomForest Regression in R r^2=", r2, sep=""))
plot(p2)
cat("Confusion matrix helada/no helada",pred_sensores[2],"\n")
y <- cut(test.set[,"y"], breaks = breaks.binario)
y_pred <- cut(pred, breaks = breaks.binario)
print(confusionMatrix(y_pred,y))
cat("Confusion matrix ",pred_sensores[i],"\n")
y <- cut(test.set[, "y"], breaks = my.breaks)
y_pred <- cut(pred, breaks = my.breaks)
print(confusionMatrix(y_pred,y))
}## Variable S10.min_t MSE: 5.582342 Rsquared: 0.8335908
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 10 2
## (0,50] 10 132
##
## Accuracy : 0.9221
## 95% CI : (0.8678, 0.9591)
## No Information Rate : 0.8701
## P-Value [Acc > NIR] : 0.03001
##
## Kappa : 0.5845
## Mcnemar's Test P-Value : 0.04331
##
## Sensitivity : 0.50000
## Specificity : 0.98507
## Pos Pred Value : 0.83333
## Neg Pred Value : 0.92958
## Prevalence : 0.12987
## Detection Rate : 0.06494
## Detection Prevalence : 0.07792
## Balanced Accuracy : 0.74254
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S10.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 10 2 0 0 0
## (0,2] 1 6 6 4 1 0
## (2,5] 0 3 4 7 7 0
## (5,10] 0 0 3 5 31 4
## (10,50] 0 0 0 0 13 47
##
## Overall Statistics
##
## Accuracy : 0.6558
## 95% CI : (0.5751, 0.7304)
## No Information Rate : 0.3377
## P-Value [Acc > NIR] : 8.142e-16
##
## Kappa : 0.5359
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.52632 0.40000
## Specificity 1.000000 0.98519 0.91367
## Pos Pred Value NaN 0.83333 0.33333
## Neg Pred Value 0.993506 0.93662 0.93382
## Prevalence 0.006494 0.12338 0.09740
## Detection Rate 0.000000 0.06494 0.03896
## Detection Prevalence 0.000000 0.07792 0.11688
## Balanced Accuracy 0.500000 0.75575 0.65683
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.43750 0.5962 0.9216
## Specificity 0.89855 0.8824 0.8738
## Pos Pred Value 0.33333 0.7209 0.7833
## Neg Pred Value 0.93233 0.8108 0.9574
## Prevalence 0.10390 0.3377 0.3312
## Detection Rate 0.04545 0.2013 0.3052
## Detection Prevalence 0.13636 0.2792 0.3896
## Balanced Accuracy 0.66803 0.7393 0.8977
## Variable S11.min_t MSE: 5.244621 Rsquared: 0.8433843
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 11 1
## (0,50] 8 134
##
## Accuracy : 0.9416
## 95% CI : (0.892, 0.9729)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.006027
##
## Kappa : 0.679
## Mcnemar's Test P-Value : 0.045500
##
## Sensitivity : 0.57895
## Specificity : 0.99259
## Pos Pred Value : 0.91667
## Neg Pred Value : 0.94366
## Prevalence : 0.12338
## Detection Rate : 0.07143
## Detection Prevalence : 0.07792
## Balanced Accuracy : 0.78577
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 11 1 0 0 0
## (0,2] 0 6 7 4 1 0
## (2,5] 0 2 6 7 6 0
## (5,10] 0 0 3 6 29 4
## (10,50] 0 0 0 0 14 47
##
## Overall Statistics
##
## Accuracy : 0.6558
## 95% CI : (0.5751, 0.7304)
## No Information Rate : 0.3312
## P-Value [Acc > NIR] : < 2.2e-16
##
## Kappa : 0.5366
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.57895 0.41176
## Specificity 1 0.99259 0.91971
## Pos Pred Value NA 0.91667 0.38889
## Neg Pred Value NA 0.94366 0.92647
## Prevalence 0 0.12338 0.11039
## Detection Rate 0 0.07143 0.04545
## Detection Prevalence 0 0.07792 0.11688
## Balanced Accuracy NA 0.78577 0.66574
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.41176 0.5800 0.9216
## Specificity 0.89781 0.8750 0.8641
## Pos Pred Value 0.33333 0.6905 0.7705
## Neg Pred Value 0.92481 0.8125 0.9570
## Prevalence 0.11039 0.3247 0.3312
## Detection Rate 0.04545 0.1883 0.3052
## Detection Prevalence 0.13636 0.2727 0.3961
## Balanced Accuracy 0.65479 0.7275 0.8928
## Variable S12.min_t MSE: 5.704803 Rsquared: 0.8305174
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 5 0
## (0,50] 14 135
##
## Accuracy : 0.9091
## 95% CI : (0.8522, 0.9494)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.133147
##
## Kappa : 0.3851
## Mcnemar's Test P-Value : 0.000512
##
## Sensitivity : 0.26316
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.90604
## Prevalence : 0.12338
## Detection Rate : 0.03247
## Detection Prevalence : 0.03247
## Balanced Accuracy : 0.63158
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S12.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 5 0 0 0 0
## (0,2] 0 11 7 2 0 0
## (2,5] 0 3 6 7 7 0
## (5,10] 0 0 3 6 28 5
## (10,50] 0 0 0 0 15 49
##
## Overall Statistics
##
## Accuracy : 0.6234
## 95% CI : (0.5418, 0.7001)
## No Information Rate : 0.3506
## P-Value [Acc > NIR] : 5.257e-12
##
## Kappa : 0.4867
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.26316 0.43750
## Specificity 1 1.00000 0.90580
## Pos Pred Value NA 1.00000 0.35000
## Neg Pred Value NA 0.90604 0.93284
## Prevalence 0 0.12338 0.10390
## Detection Rate 0 0.03247 0.04545
## Detection Prevalence 0 0.03247 0.12987
## Balanced Accuracy NA 0.63158 0.67165
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.46667 0.5600 0.9074
## Specificity 0.88489 0.8654 0.8500
## Pos Pred Value 0.30435 0.6667 0.7656
## Neg Pred Value 0.93893 0.8036 0.9444
## Prevalence 0.09740 0.3247 0.3506
## Detection Rate 0.04545 0.1818 0.3182
## Detection Prevalence 0.14935 0.2727 0.4156
## Balanced Accuracy 0.67578 0.7127 0.8787
## Variable S13.min_t MSE: 5.21656 Rsquared: 0.8431951
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 5 0
## (0,50] 14 135
##
## Accuracy : 0.9091
## 95% CI : (0.8522, 0.9494)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.133147
##
## Kappa : 0.3851
## Mcnemar's Test P-Value : 0.000512
##
## Sensitivity : 0.26316
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.90604
## Prevalence : 0.12338
## Detection Rate : 0.03247
## Detection Prevalence : 0.03247
## Balanced Accuracy : 0.63158
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S13.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 5 0 0 0 0
## (0,2] 0 11 8 2 0 0
## (2,5] 0 3 4 7 7 0
## (5,10] 0 0 3 6 27 6
## (10,50] 0 0 0 0 13 52
##
## Overall Statistics
##
## Accuracy : 0.6429
## 95% CI : (0.5618, 0.7184)
## No Information Rate : 0.3766
## P-Value [Acc > NIR] : 2.065e-11
##
## Kappa : 0.5089
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.26316 0.53333
## Specificity 1 1.00000 0.90647
## Pos Pred Value NA 1.00000 0.38095
## Neg Pred Value NA 0.90604 0.94737
## Prevalence 0 0.12338 0.09740
## Detection Rate 0 0.03247 0.05195
## Detection Prevalence 0 0.03247 0.13636
## Balanced Accuracy NA 0.63158 0.71990
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.46667 0.5745 0.8966
## Specificity 0.89928 0.8598 0.8646
## Pos Pred Value 0.33333 0.6429 0.8000
## Neg Pred Value 0.93985 0.8214 0.9326
## Prevalence 0.09740 0.3052 0.3766
## Detection Rate 0.04545 0.1753 0.3377
## Detection Prevalence 0.13636 0.2727 0.4221
## Balanced Accuracy 0.68297 0.7171 0.8806
## Variable S14.min_t MSE: 5.219279 Rsquared: 0.8411804
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 7 0
## (0,50] 12 135
##
## Accuracy : 0.9221
## 95% CI : (0.8678, 0.9591)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.049328
##
## Kappa : 0.5056
## Mcnemar's Test P-Value : 0.001496
##
## Sensitivity : 0.36842
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.91837
## Prevalence : 0.12338
## Detection Rate : 0.04545
## Detection Prevalence : 0.04545
## Balanced Accuracy : 0.68421
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S14.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 7 0 0 0 0
## (0,2] 1 8 7 4 0 0
## (2,5] 0 3 5 6 8 0
## (5,10] 0 0 3 6 29 4
## (10,50] 0 0 0 0 13 50
##
## Overall Statistics
##
## Accuracy : 0.6429
## 95% CI : (0.5618, 0.7184)
## No Information Rate : 0.3506
## P-Value [Acc > NIR] : 1.57e-13
##
## Kappa : 0.5142
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.38889 0.46667
## Specificity 1.000000 1.00000 0.90647
## Pos Pred Value NaN 1.00000 0.35000
## Neg Pred Value 0.993506 0.92517 0.94030
## Prevalence 0.006494 0.11688 0.09740
## Detection Rate 0.000000 0.04545 0.04545
## Detection Prevalence 0.000000 0.04545 0.12987
## Balanced Accuracy 0.500000 0.69444 0.68657
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.37500 0.5800 0.9259
## Specificity 0.88406 0.8750 0.8700
## Pos Pred Value 0.27273 0.6905 0.7937
## Neg Pred Value 0.92424 0.8125 0.9560
## Prevalence 0.10390 0.3247 0.3506
## Detection Rate 0.03896 0.1883 0.3247
## Detection Prevalence 0.14286 0.2727 0.4091
## Balanced Accuracy 0.62953 0.7275 0.8980
## Variable S15.min_t MSE: 5.194801 Rsquared: 0.8390262
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 11 2
## (0,50] 8 133
##
## Accuracy : 0.9351
## 95% CI : (0.8838, 0.9684)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.01333
##
## Kappa : 0.6527
## Mcnemar's Test P-Value : 0.11385
##
## Sensitivity : 0.57895
## Specificity : 0.98519
## Pos Pred Value : 0.84615
## Neg Pred Value : 0.94326
## Prevalence : 0.12338
## Detection Rate : 0.07143
## Detection Prevalence : 0.08442
## Balanced Accuracy : 0.78207
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S15.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 11 2 0 0 0
## (0,2] 0 6 6 5 1 0
## (2,5] 0 2 5 8 5 0
## (5,10] 0 0 3 6 30 5
## (10,50] 0 0 0 0 15 44
##
## Overall Statistics
##
## Accuracy : 0.6429
## 95% CI : (0.5618, 0.7184)
## No Information Rate : 0.3312
## P-Value [Acc > NIR] : 2.691e-15
##
## Kappa : 0.5205
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.57895 0.37500
## Specificity 1 0.98519 0.91304
## Pos Pred Value NA 0.84615 0.33333
## Neg Pred Value NA 0.94326 0.92647
## Prevalence 0 0.12338 0.10390
## Detection Rate 0 0.07143 0.03896
## Detection Prevalence 0 0.08442 0.11688
## Balanced Accuracy NA 0.78207 0.64402
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.42105 0.5882 0.8980
## Specificity 0.91111 0.8641 0.8571
## Pos Pred Value 0.40000 0.6818 0.7458
## Neg Pred Value 0.91791 0.8091 0.9474
## Prevalence 0.12338 0.3312 0.3182
## Detection Rate 0.05195 0.1948 0.2857
## Detection Prevalence 0.12987 0.2857 0.3831
## Balanced Accuracy 0.66608 0.7262 0.8776
## Variable S16.min_t MSE: 6.051524 Rsquared: 0.8143333
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 5 0
## (0,50] 11 138
##
## Accuracy : 0.9286
## 95% CI : (0.8758, 0.9638)
## No Information Rate : 0.8961
## P-Value [Acc > NIR] : 0.113686
##
## Kappa : 0.4489
## Mcnemar's Test P-Value : 0.002569
##
## Sensitivity : 0.31250
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.92617
## Prevalence : 0.10390
## Detection Rate : 0.03247
## Detection Prevalence : 0.03247
## Balanced Accuracy : 0.65625
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S16.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 5 0 0 0 0
## (0,2] 0 10 4 3 0 0
## (2,5] 0 1 6 11 7 0
## (5,10] 0 0 3 7 23 5
## (10,50] 0 0 0 0 17 52
##
## Overall Statistics
##
## Accuracy : 0.6169
## 95% CI : (0.5352, 0.694)
## No Information Rate : 0.3701
## P-Value [Acc > NIR] : 4.724e-10
##
## Kappa : 0.4709
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.31250 0.30769
## Specificity 1 1.00000 0.90780
## Pos Pred Value NA 1.00000 0.23529
## Neg Pred Value NA 0.92617 0.93431
## Prevalence 0 0.10390 0.08442
## Detection Rate 0 0.03247 0.02597
## Detection Prevalence 0 0.03247 0.11039
## Balanced Accuracy NA 0.65625 0.60775
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.52381 0.4894 0.9123
## Specificity 0.89474 0.8598 0.8247
## Pos Pred Value 0.44000 0.6053 0.7536
## Neg Pred Value 0.92248 0.7931 0.9412
## Prevalence 0.13636 0.3052 0.3701
## Detection Rate 0.07143 0.1494 0.3377
## Detection Prevalence 0.16234 0.2468 0.4481
## Balanced Accuracy 0.70927 0.6746 0.8685
## Variable S18.min_t MSE: 5.372794 Rsquared: 0.8389333
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 8 2
## (0,50] 11 133
##
## Accuracy : 0.9156
## 95% CI : (0.86, 0.9543)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.0840
##
## Kappa : 0.51
## Mcnemar's Test P-Value : 0.0265
##
## Sensitivity : 0.42105
## Specificity : 0.98519
## Pos Pred Value : 0.80000
## Neg Pred Value : 0.92361
## Prevalence : 0.12338
## Detection Rate : 0.05195
## Detection Prevalence : 0.06494
## Balanced Accuracy : 0.70312
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S18.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 8 2 0 0 0
## (0,2] 0 8 6 3 1 0
## (2,5] 0 3 5 8 6 0
## (5,10] 0 0 3 5 29 5
## (10,50] 0 0 0 0 14 48
##
## Overall Statistics
##
## Accuracy : 0.6429
## 95% CI : (0.5618, 0.7184)
## No Information Rate : 0.3442
## P-Value [Acc > NIR] : 4.217e-14
##
## Kappa : 0.516
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.42105 0.37500
## Specificity 1 0.98519 0.91304
## Pos Pred Value NA 0.80000 0.33333
## Neg Pred Value NA 0.92361 0.92647
## Prevalence 0 0.12338 0.10390
## Detection Rate 0 0.05195 0.03896
## Detection Prevalence 0 0.06494 0.11688
## Balanced Accuracy NA 0.70312 0.64402
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.50000 0.5800 0.9057
## Specificity 0.89855 0.8750 0.8614
## Pos Pred Value 0.36364 0.6905 0.7742
## Neg Pred Value 0.93939 0.8125 0.9457
## Prevalence 0.10390 0.3247 0.3442
## Detection Rate 0.05195 0.1883 0.3117
## Detection Prevalence 0.14286 0.2727 0.4026
## Balanced Accuracy 0.69928 0.7275 0.8835
## Variable S19.min_t MSE: 5.536262 Rsquared: 0.8364076
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 7 0
## (0,50] 12 135
##
## Accuracy : 0.9221
## 95% CI : (0.8678, 0.9591)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.049328
##
## Kappa : 0.5056
## Mcnemar's Test P-Value : 0.001496
##
## Sensitivity : 0.36842
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.91837
## Prevalence : 0.12338
## Detection Rate : 0.04545
## Detection Prevalence : 0.04545
## Balanced Accuracy : 0.68421
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S19.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 7 0 0 0 0
## (0,2] 0 9 6 3 0 0
## (2,5] 0 3 6 7 8 0
## (5,10] 0 0 3 6 29 5
## (10,50] 0 0 0 0 12 50
##
## Overall Statistics
##
## Accuracy : 0.6429
## 95% CI : (0.5618, 0.7184)
## No Information Rate : 0.3571
## P-Value [Acc > NIR] : 5.624e-13
##
## Kappa : 0.5136
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.36842 0.40000
## Specificity 1 1.00000 0.91367
## Pos Pred Value NA 1.00000 0.33333
## Neg Pred Value NA 0.91837 0.93382
## Prevalence 0 0.12338 0.09740
## Detection Rate 0 0.04545 0.03896
## Detection Prevalence 0 0.04545 0.11688
## Balanced Accuracy NA 0.68421 0.65683
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.43750 0.5918 0.9091
## Specificity 0.87681 0.8667 0.8788
## Pos Pred Value 0.29167 0.6744 0.8065
## Neg Pred Value 0.93077 0.8198 0.9457
## Prevalence 0.10390 0.3182 0.3571
## Detection Rate 0.04545 0.1883 0.3247
## Detection Prevalence 0.15584 0.2792 0.4026
## Balanced Accuracy 0.65716 0.7293 0.8939
## Variable S1.min_t MSE: 5.345799 Rsquared: 0.8447577
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 9 1
## (0,50] 10 134
##
## Accuracy : 0.9286
## 95% CI : (0.8758, 0.9638)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.02677
##
## Kappa : 0.5854
## Mcnemar's Test P-Value : 0.01586
##
## Sensitivity : 0.47368
## Specificity : 0.99259
## Pos Pred Value : 0.90000
## Neg Pred Value : 0.93056
## Prevalence : 0.12338
## Detection Rate : 0.05844
## Detection Prevalence : 0.06494
## Balanced Accuracy : 0.73314
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S1.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 9 1 0 0 0
## (0,2] 0 7 7 4 1 0
## (2,5] 0 3 5 7 7 0
## (5,10] 0 0 3 6 28 4
## (10,50] 0 0 0 0 11 51
##
## Overall Statistics
##
## Accuracy : 0.6623
## 95% CI : (0.5818, 0.7365)
## No Information Rate : 0.3571
## P-Value [Acc > NIR] : 1.423e-14
##
## Kappa : 0.5427
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.47368 0.43750
## Specificity 1 0.99259 0.91304
## Pos Pred Value NA 0.90000 0.36842
## Neg Pred Value NA 0.93056 0.93333
## Prevalence 0 0.12338 0.10390
## Detection Rate 0 0.05844 0.04545
## Detection Prevalence 0 0.06494 0.12338
## Balanced Accuracy NA 0.73314 0.67527
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.41176 0.5957 0.9273
## Specificity 0.89051 0.8785 0.8889
## Pos Pred Value 0.31818 0.6829 0.8226
## Neg Pred Value 0.92424 0.8319 0.9565
## Prevalence 0.11039 0.3052 0.3571
## Detection Rate 0.04545 0.1818 0.3312
## Detection Prevalence 0.14286 0.2662 0.4026
## Balanced Accuracy 0.65114 0.7371 0.9081
## Variable S20.min_t MSE: 5.300958 Rsquared: 0.8433489
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 6 0
## (0,50] 13 135
##
## Accuracy : 0.9156
## 95% CI : (0.86, 0.9543)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.0840000
##
## Kappa : 0.4473
## Mcnemar's Test P-Value : 0.0008741
##
## Sensitivity : 0.31579
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.91216
## Prevalence : 0.12338
## Detection Rate : 0.03896
## Detection Prevalence : 0.03896
## Balanced Accuracy : 0.65789
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S20.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 6 0 0 0 0
## (0,2] 1 9 6 4 1 0
## (2,5] 0 3 6 5 6 0
## (5,10] 0 0 3 6 28 6
## (10,50] 0 0 0 0 12 52
##
## Overall Statistics
##
## Accuracy : 0.6299
## 95% CI : (0.5484, 0.7062)
## No Information Rate : 0.3766
## P-Value [Acc > NIR] : 1.768e-10
##
## Kappa : 0.4914
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.33333 0.40000
## Specificity 1.000000 1.00000 0.89209
## Pos Pred Value NaN 1.00000 0.28571
## Neg Pred Value 0.993506 0.91892 0.93233
## Prevalence 0.006494 0.11688 0.09740
## Detection Rate 0.000000 0.03896 0.03896
## Detection Prevalence 0.000000 0.03896 0.13636
## Balanced Accuracy 0.500000 0.66667 0.64604
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.33333 0.5957 0.8966
## Specificity 0.89209 0.8598 0.8750
## Pos Pred Value 0.25000 0.6512 0.8125
## Neg Pred Value 0.92537 0.8288 0.9333
## Prevalence 0.09740 0.3052 0.3766
## Detection Rate 0.03247 0.1818 0.3377
## Detection Prevalence 0.12987 0.2792 0.4156
## Balanced Accuracy 0.61271 0.7278 0.8858
## Variable S2.min_t MSE: 5.316701 Rsquared: 0.8387682
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 6 0
## (0,50] 12 136
##
## Accuracy : 0.9221
## 95% CI : (0.8678, 0.9591)
## No Information Rate : 0.8831
## P-Value [Acc > NIR] : 0.078473
##
## Kappa : 0.469
## Mcnemar's Test P-Value : 0.001496
##
## Sensitivity : 0.33333
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.91892
## Prevalence : 0.11688
## Detection Rate : 0.03896
## Detection Prevalence : 0.03896
## Balanced Accuracy : 0.66667
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S2.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 6 0 0 0 0
## (0,2] 0 10 4 6 0 0
## (2,5] 0 2 7 6 7 0
## (5,10] 0 0 3 7 27 4
## (10,50] 0 0 0 0 14 51
##
## Overall Statistics
##
## Accuracy : 0.6104
## 95% CI : (0.5286, 0.6878)
## No Information Rate : 0.3571
## P-Value [Acc > NIR] : 1.485e-10
##
## Kappa : 0.468
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.33333 0.28571
## Specificity 1 1.00000 0.88571
## Pos Pred Value NA 1.00000 0.20000
## Neg Pred Value NA 0.91892 0.92537
## Prevalence 0 0.11688 0.09091
## Detection Rate 0 0.03896 0.02597
## Detection Prevalence 0 0.03896 0.12987
## Balanced Accuracy NA 0.66667 0.58571
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.31579 0.5625 0.9273
## Specificity 0.88148 0.8679 0.8586
## Pos Pred Value 0.27273 0.6585 0.7846
## Neg Pred Value 0.90152 0.8142 0.9551
## Prevalence 0.12338 0.3117 0.3571
## Detection Rate 0.03896 0.1753 0.3312
## Detection Prevalence 0.14286 0.2662 0.4221
## Balanced Accuracy 0.59864 0.7152 0.8929
## Variable S3.min_t MSE: 5.175089 Rsquared: 0.8454053
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 5 0
## (0,50] 11 138
##
## Accuracy : 0.9286
## 95% CI : (0.8758, 0.9638)
## No Information Rate : 0.8961
## P-Value [Acc > NIR] : 0.113686
##
## Kappa : 0.4489
## Mcnemar's Test P-Value : 0.002569
##
## Sensitivity : 0.31250
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.92617
## Prevalence : 0.10390
## Detection Rate : 0.03247
## Detection Prevalence : 0.03247
## Balanced Accuracy : 0.65625
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S3.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 5 0 0 0 0
## (0,2] 0 10 7 2 0 0
## (2,5] 0 1 9 7 6 0
## (5,10] 0 0 3 7 27 5
## (10,50] 0 0 0 0 8 57
##
## Overall Statistics
##
## Accuracy : 0.6688
## 95% CI : (0.5885, 0.7425)
## No Information Rate : 0.4026
## P-Value [Acc > NIR] : 2.324e-11
##
## Kappa : 0.5422
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.31250 0.36842
## Specificity 1 1.00000 0.91111
## Pos Pred Value NA 1.00000 0.36842
## Neg Pred Value NA 0.92617 0.91111
## Prevalence 0 0.10390 0.12338
## Detection Rate 0 0.03247 0.04545
## Detection Prevalence 0 0.03247 0.12338
## Balanced Accuracy NA 0.65625 0.63977
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.43750 0.6585 0.9194
## Specificity 0.88406 0.8673 0.9130
## Pos Pred Value 0.30435 0.6429 0.8769
## Neg Pred Value 0.93130 0.8750 0.9438
## Prevalence 0.10390 0.2662 0.4026
## Detection Rate 0.04545 0.1753 0.3701
## Detection Prevalence 0.14935 0.2727 0.4221
## Balanced Accuracy 0.66078 0.7629 0.9162
## Variable S4.min_t MSE: 5.052811 Rsquared: 0.8500618
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 9 3
## (0,50] 9 133
##
## Accuracy : 0.9221
## 95% CI : (0.8678, 0.9591)
## No Information Rate : 0.8831
## P-Value [Acc > NIR] : 0.07847
##
## Kappa : 0.5587
## Mcnemar's Test P-Value : 0.14891
##
## Sensitivity : 0.50000
## Specificity : 0.97794
## Pos Pred Value : 0.75000
## Neg Pred Value : 0.93662
## Prevalence : 0.11688
## Detection Rate : 0.05844
## Detection Prevalence : 0.07792
## Balanced Accuracy : 0.73897
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S4.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 9 3 0 0 0
## (0,2] 0 6 7 3 1 0
## (2,5] 0 3 5 8 6 0
## (5,10] 0 0 3 6 27 5
## (10,50] 0 0 0 0 14 48
##
## Overall Statistics
##
## Accuracy : 0.6429
## 95% CI : (0.5618, 0.7184)
## No Information Rate : 0.3442
## P-Value [Acc > NIR] : 4.217e-14
##
## Kappa : 0.5178
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.50000 0.38889
## Specificity 1 0.97794 0.92647
## Pos Pred Value NA 0.75000 0.41176
## Neg Pred Value NA 0.93662 0.91971
## Prevalence 0 0.11688 0.11688
## Detection Rate 0 0.05844 0.04545
## Detection Prevalence 0 0.07792 0.11039
## Balanced Accuracy NA 0.73897 0.65768
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.47059 0.5625 0.9057
## Specificity 0.89781 0.8679 0.8614
## Pos Pred Value 0.36364 0.6585 0.7742
## Neg Pred Value 0.93182 0.8142 0.9457
## Prevalence 0.11039 0.3117 0.3442
## Detection Rate 0.05195 0.1753 0.3117
## Detection Prevalence 0.14286 0.2662 0.4026
## Balanced Accuracy 0.68420 0.7152 0.8835
## Variable S5.min_t MSE: 5.669448 Rsquared: 0.8392756
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 8 1
## (0,50] 12 133
##
## Accuracy : 0.9156
## 95% CI : (0.86, 0.9543)
## No Information Rate : 0.8701
## P-Value [Acc > NIR] : 0.053683
##
## Kappa : 0.5124
## Mcnemar's Test P-Value : 0.005546
##
## Sensitivity : 0.40000
## Specificity : 0.99254
## Pos Pred Value : 0.88889
## Neg Pred Value : 0.91724
## Prevalence : 0.12987
## Detection Rate : 0.05195
## Detection Prevalence : 0.05844
## Balanced Accuracy : 0.69627
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S5.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 8 1 0 0 0
## (0,2] 1 7 7 4 0 0
## (2,5] 0 4 4 5 7 0
## (5,10] 0 0 3 6 29 5
## (10,50] 0 0 0 0 11 52
##
## Overall Statistics
##
## Accuracy : 0.6558
## 95% CI : (0.5751, 0.7304)
## No Information Rate : 0.3701
## P-Value [Acc > NIR] : 6.378e-13
##
## Kappa : 0.5295
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.42105 0.46667
## Specificity 1.000000 0.99259 0.91367
## Pos Pred Value NaN 0.88889 0.36842
## Neg Pred Value 0.993506 0.92414 0.94074
## Prevalence 0.006494 0.12338 0.09740
## Detection Rate 0.000000 0.05195 0.04545
## Detection Prevalence 0.000000 0.05844 0.12338
## Balanced Accuracy 0.500000 0.70682 0.69017
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.33333 0.6170 0.9123
## Specificity 0.89209 0.8692 0.8866
## Pos Pred Value 0.25000 0.6744 0.8254
## Neg Pred Value 0.92537 0.8378 0.9451
## Prevalence 0.09740 0.3052 0.3701
## Detection Rate 0.03247 0.1883 0.3377
## Detection Prevalence 0.12987 0.2792 0.4091
## Balanced Accuracy 0.61271 0.7431 0.8994
## Variable S6.min_t MSE: 5.277193 Rsquared: 0.846052
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 5 0
## (0,50] 12 137
##
## Accuracy : 0.9221
## 95% CI : (0.8678, 0.9591)
## No Information Rate : 0.8896
## P-Value [Acc > NIR] : 0.120600
##
## Kappa : 0.4257
## Mcnemar's Test P-Value : 0.001496
##
## Sensitivity : 0.29412
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.91946
## Prevalence : 0.11039
## Detection Rate : 0.03247
## Detection Prevalence : 0.03247
## Balanced Accuracy : 0.64706
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S6.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 5 0 0 0 0
## (0,2] 0 11 5 4 0 0
## (2,5] 0 1 7 6 8 0
## (5,10] 0 0 3 6 26 6
## (10,50] 0 0 0 0 9 57
##
## Overall Statistics
##
## Accuracy : 0.6429
## 95% CI : (0.5618, 0.7184)
## No Information Rate : 0.4091
## P-Value [Acc > NIR] : 4.206e-09
##
## Kappa : 0.5035
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.29412 0.33333
## Specificity 1 1.00000 0.89209
## Pos Pred Value NA 1.00000 0.25000
## Neg Pred Value NA 0.91946 0.92537
## Prevalence 0 0.11039 0.09740
## Detection Rate 0 0.03247 0.03247
## Detection Prevalence 0 0.03247 0.12987
## Balanced Accuracy NA 0.64706 0.61271
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.37500 0.6047 0.9048
## Specificity 0.88406 0.8649 0.9011
## Pos Pred Value 0.27273 0.6341 0.8636
## Neg Pred Value 0.92424 0.8496 0.9318
## Prevalence 0.10390 0.2792 0.4091
## Detection Rate 0.03896 0.1688 0.3701
## Detection Prevalence 0.14286 0.2662 0.4286
## Balanced Accuracy 0.62953 0.7348 0.9029
## Variable S7.min_t MSE: 5.589131 Rsquared: 0.8343217
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 10 1
## (0,50] 11 132
##
## Accuracy : 0.9221
## 95% CI : (0.8678, 0.9591)
## No Information Rate : 0.8636
## P-Value [Acc > NIR] : 0.017697
##
## Kappa : 0.5862
## Mcnemar's Test P-Value : 0.009375
##
## Sensitivity : 0.47619
## Specificity : 0.99248
## Pos Pred Value : 0.90909
## Neg Pred Value : 0.92308
## Prevalence : 0.13636
## Detection Rate : 0.06494
## Detection Prevalence : 0.07143
## Balanced Accuracy : 0.73434
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S7.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 10 1 0 0 0
## (0,2] 1 7 7 3 1 0
## (2,5] 0 3 4 7 7 0
## (5,10] 0 0 3 7 28 5
## (10,50] 0 0 0 0 12 48
##
## Overall Statistics
##
## Accuracy : 0.6494
## 95% CI : (0.5684, 0.7244)
## No Information Rate : 0.3442
## P-Value [Acc > NIR] : 1.204e-14
##
## Kappa : 0.5278
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.50000 0.46667
## Specificity 1.000000 0.99254 0.91367
## Pos Pred Value NaN 0.90909 0.36842
## Neg Pred Value 0.993506 0.93007 0.94074
## Prevalence 0.006494 0.12987 0.09740
## Detection Rate 0.000000 0.06494 0.04545
## Detection Prevalence 0.000000 0.07143 0.12338
## Balanced Accuracy 0.500000 0.74627 0.69017
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.41176 0.5833 0.9057
## Specificity 0.89781 0.8585 0.8812
## Pos Pred Value 0.33333 0.6512 0.8000
## Neg Pred Value 0.92481 0.8198 0.9468
## Prevalence 0.11039 0.3117 0.3442
## Detection Rate 0.04545 0.1818 0.3117
## Detection Prevalence 0.13636 0.2792 0.3896
## Balanced Accuracy 0.65479 0.7209 0.8934
## Variable S8.min_t MSE: 5.618876 Rsquared: 0.8327185
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 6 0
## (0,50] 13 135
##
## Accuracy : 0.9156
## 95% CI : (0.86, 0.9543)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.0840000
##
## Kappa : 0.4473
## Mcnemar's Test P-Value : 0.0008741
##
## Sensitivity : 0.31579
## Specificity : 1.00000
## Pos Pred Value : 1.00000
## Neg Pred Value : 0.91216
## Prevalence : 0.12338
## Detection Rate : 0.03896
## Detection Prevalence : 0.03896
## Balanced Accuracy : 0.65789
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S8.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 6 0 0 0 0
## (0,2] 0 10 7 3 0 0
## (2,5] 0 3 5 7 8 0
## (5,10] 0 0 3 7 28 5
## (10,50] 0 0 0 0 14 48
##
## Overall Statistics
##
## Accuracy : 0.6234
## 95% CI : (0.5418, 0.7001)
## No Information Rate : 0.3442
## P-Value [Acc > NIR] : 1.536e-12
##
## Kappa : 0.4889
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.31579 0.46667
## Specificity 1 1.00000 0.90647
## Pos Pred Value NA 1.00000 0.35000
## Neg Pred Value NA 0.91216 0.94030
## Prevalence 0 0.12338 0.09740
## Detection Rate 0 0.03896 0.04545
## Detection Prevalence 0 0.03896 0.12987
## Balanced Accuracy NA 0.65789 0.68657
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.41176 0.5600 0.9057
## Specificity 0.88321 0.8558 0.8614
## Pos Pred Value 0.30435 0.6512 0.7742
## Neg Pred Value 0.92366 0.8018 0.9457
## Prevalence 0.11039 0.3247 0.3442
## Detection Rate 0.04545 0.1818 0.3117
## Detection Prevalence 0.14935 0.2792 0.4026
## Balanced Accuracy 0.64749 0.7079 0.8835
## Variable S9.min_t MSE: 5.824682 Rsquared: 0.8242227
## Confusion matrix helada/no helada S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 10 2
## (0,50] 11 131
##
## Accuracy : 0.9156
## 95% CI : (0.86, 0.9543)
## No Information Rate : 0.8636
## P-Value [Acc > NIR] : 0.03322
##
## Kappa : 0.5627
## Mcnemar's Test P-Value : 0.02650
##
## Sensitivity : 0.47619
## Specificity : 0.98496
## Pos Pred Value : 0.83333
## Neg Pred Value : 0.92254
## Prevalence : 0.13636
## Detection Rate : 0.06494
## Detection Prevalence : 0.07792
## Balanced Accuracy : 0.73058
##
## 'Positive' Class : (-10,0]
##
## Confusion matrix S9.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 1 9 2 0 0 0
## (0,2] 1 6 7 3 1 0
## (2,5] 0 3 4 8 7 0
## (5,10] 0 1 2 6 29 5
## (10,50] 0 0 0 0 14 45
##
## Overall Statistics
##
## Accuracy : 0.6364
## 95% CI : (0.5551, 0.7123)
## No Information Rate : 0.3312
## P-Value [Acc > NIR] : 9.71e-15
##
## Kappa : 0.5128
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.00000 0.47368 0.46667
## Specificity 1.00000 0.97778 0.92086
## Pos Pred Value NaN 0.75000 0.38889
## Neg Pred Value 0.98701 0.92958 0.94118
## Prevalence 0.01299 0.12338 0.09740
## Detection Rate 0.00000 0.05844 0.04545
## Detection Prevalence 0.00000 0.07792 0.11688
## Balanced Accuracy 0.50000 0.72573 0.69376
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.47059 0.5686 0.9000
## Specificity 0.89781 0.8641 0.8654
## Pos Pred Value 0.36364 0.6744 0.7627
## Neg Pred Value 0.93182 0.8018 0.9474
## Prevalence 0.11039 0.3312 0.3247
## Detection Rate 0.05195 0.1883 0.2922
## Detection Prevalence 0.14286 0.2792 0.3831
## Balanced Accuracy 0.68420 0.7164 0.8827Oversampling: generamos más datos en el training.set mediante SMOTE
Para ello dividimos el dataset entre training y testing. En el training set aplicamos SMOTE.
#genero etiquetas: 1 noche de helada y 0 no helada
Y_class <- as.factor(with(df,ifelse(S20.min_t <= 0,1,0)))
hasta <- round(nrow(df)*.67)
hasta## [1] 310summary(Y_class[hasta:length(Y_class)])## 0 1
## 135 19test.set <- df[hasta:nrow(df),]library(unbalanced)## Loading required package: mlr## Loading required package: ParamHelpers## Warning: replacing previous import 'BBmisc::isFALSE' by
## 'backports::isFALSE' when loading 'mlr'##
## Attaching package: 'mlr'## The following object is masked _by_ '.GlobalEnv':
##
## mse## The following object is masked from 'package:caret':
##
## train## Loading required package: foreach## Loading required package: doParallel## Loading required package: iterators## Loading required package: paralleldatos para entrenar
data_smote <- ubBalance(df[1:hasta,],Y_class[1:hasta],type = "ubSMOTE",percOver = 300, percUnder = 150)para visualizar la distribución de las clases
summary(data_smote$Y)## 0 1
## 193 172training.set <- data_smote$XProcedemos a realizar las predicciones y evaluar el error.
Aprendemos una red bayesiana usando el algoritmo hc y pasando como restricciones las white y black lists
start_time <- Sys.time()
print(start_time)## [1] "2017-10-10 14:16:32 ART"res = hc(training.set, whitelist=wl,blacklist = bl) # , cluster = cl) # no funciona esta funcion de cluster
end_time <- Sys.time()
end_time - start_time## Time difference of 1.470029 hourssave(res, file=paste("hc-tminchaar-smote-",Sys.time(),".RData",sep=""))Aprendizaje de parametros
start_time <- Sys.time()
fitted = bn.fit(res, training.set) # learning of parameters
end_time <- Sys.time()
end_time - start_time## Time difference of 0.488565 secsMostramos los parámetros para los nodos que nos interesan predecir
fitted[pred_sensores]## $S10.min_t
##
## Parameters of node S10.min_t (Gaussian distribution)
##
## Conditional density: S10.min_t | S10.max_T_2 + S11.max_T_2 + S12.max_T_2 + S14.max_T_2 + S15.max_T_2 + S16.max_T_2 + S17.max_T_2 + S18.max_T_2 + S20.max_T_2 + S2.max_T_2 + S3.max_T_2 + S5.max_T_2 + S6.max_T_2 + S8.max_T_2 + S10.media_T_2 + S11.media_T_2 + S12.media_T_2 + S13.media_T_2 + S15.media_T_2 + S17.media_T_2 + S18.media_T_2 + S20.media_T_2 + S2.media_T_2 + S3.media_T_2 + S4.media_T_2 + S6.media_T_2 + S7.media_T_2 + S8.media_T_2 + S9.media_T_2 + S10.min_T_2 + S12.min_T_2 + S15.min_T_2 + S16.min_T_2 + S17.min_T_2 + S18.min_T_2 + S1.min_T_2 + S20.min_T_2 + S2.min_T_2 + S3.min_T_2 + S4.min_T_2 + S5.min_T_2 + S7.min_T_2 + S8.min_T_2 + S9.min_T_2 + S10.15hs_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S16.15hs_T_2 + S17.15hs_T_2 + S18.15hs_T_2 + S19.15hs_T_2 + S1.15hs_T_2 + S2.15hs_T_2 + S4.15hs_T_2 + S5.15hs_T_2 + S8.15hs_T_2 + S9.15hs_T_2 + S10.12hs_T_2 + S11.12hs_T_2 + S12.12hs_T_2 + S14.12hs_T_2 + S15.12hs_T_2 + S16.12hs_T_2 + S17.12hs_T_2 + S1.12hs_T_2 + S20.12hs_T_2 + S2.12hs_T_2 + S3.12hs_T_2 + S5.12hs_T_2 + S9.12hs_T_2 + S10.18hs_T_2 + S11.18hs_T_2 + S14.18hs_T_2 + S16.18hs_T_2 + S17.18hs_T_2 + S18.18hs_T_2 + S1.18hs_T_2 + S2.18hs_T_2 + S3.18hs_T_2 + S4.18hs_T_2 + S6.18hs_T_2 + S7.18hs_T_2 + S8.18hs_T_2 + S9.18hs_T_2 + Est.humedad_min_T_2 + Est.humedad_med_T_2 + S10.max_T_1 + S11.max_T_1 + S15.max_T_1 + S18.max_T_1 + S19.max_T_1 + S20.max_T_1 + S2.max_T_1 + S3.max_T_1 + S4.max_T_1 + S7.max_T_1 + S8.max_T_1 + S9.max_T_1 + S10.media_T_1 + S13.media_T_1 + S15.media_T_1 + S16.media_T_1 + S18.media_T_1 + S20.media_T_1 + S2.media_T_1 + S3.media_T_1 + S4.media_T_1 + S5.media_T_1 + S6.media_T_1 + S7.media_T_1 + S8.media_T_1 + S10.min_T_1 + S11.min_T_1 + S12.min_T_1 + S13.min_T_1 + S14.min_T_1 + S16.min_T_1 + S18.min_T_1 + S19.min_T_1 + S20.min_T_1 + S2.min_T_1 + S3.min_T_1 + S4.min_T_1 + S5.min_T_1 + S6.min_T_1 + S7.min_T_1 + S8.min_T_1 + S9.min_T_1 + S10.15hs_T_1 + S12.15hs_T_1 + S13.15hs_T_1 + S14.15hs_T_1 + S17.15hs_T_1 + S19.15hs_T_1 + S1.15hs_T_1 + S20.15hs_T_1 + S3.15hs_T_1 + S4.15hs_T_1 + S8.15hs_T_1 + S9.15hs_T_1 + S10.12hs_T_1 + S13.12hs_T_1 + S14.12hs_T_1 + S15.12hs_T_1 + S16.12hs_T_1 + S17.12hs_T_1 + S19.12hs_T_1 + S1.12hs_T_1 + S20.12hs_T_1 + S2.12hs_T_1 + S3.12hs_T_1 + S4.12hs_T_1 + S5.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S9.12hs_T_1 + S10.18hs_T_1 + S11.18hs_T_1 + S12.18hs_T_1 + S13.18hs_T_1 + S14.18hs_T_1 + S15.18hs_T_1 + S16.18hs_T_1 + S17.18hs_T_1 + S18.18hs_T_1 + S19.18hs_T_1 + S1.18hs_T_1 + S2.18hs_T_1 + S3.18hs_T_1 + S5.18hs_T_1 + S6.18hs_T_1 + S7.18hs_T_1 + Est.temp_min_T_1 + Est.temp_max_T_1 + Est.temp_med_T_1
## Coefficients:
## (Intercept) S10.max_T_2 S11.max_T_2
## -5.845298e+00 -3.302219e-01 -9.610543e-03
## S12.max_T_2 S14.max_T_2 S15.max_T_2
## 1.096586e+00 1.122881e+00 -1.206700e+00
## S16.max_T_2 S17.max_T_2 S18.max_T_2
## 2.673962e-01 2.800254e+00 -8.323331e-02
## S20.max_T_2 S2.max_T_2 S3.max_T_2
## 2.383455e+00 -7.748601e-01 -2.042700e+00
## S5.max_T_2 S6.max_T_2 S8.max_T_2
## -2.772505e+00 -1.113023e+00 1.639107e-01
## S10.media_T_2 S11.media_T_2 S12.media_T_2
## -5.107192e+00 2.243017e-01 1.796721e+00
## S13.media_T_2 S15.media_T_2 S17.media_T_2
## 1.268966e-01 -5.343294e+00 -5.469976e+00
## S18.media_T_2 S20.media_T_2 S2.media_T_2
## -4.875785e+00 9.718330e+00 -5.648851e+00
## S3.media_T_2 S4.media_T_2 S6.media_T_2
## -1.032096e+00 9.890294e+00 -4.058260e+00
## S7.media_T_2 S8.media_T_2 S9.media_T_2
## 9.249380e+00 4.216950e-01 1.065825e+00
## S10.min_T_2 S12.min_T_2 S15.min_T_2
## 6.288777e-01 7.090183e-01 -1.707065e+00
## S16.min_T_2 S17.min_T_2 S18.min_T_2
## -5.321426e-01 1.800761e-01 8.114053e-01
## S1.min_T_2 S20.min_T_2 S2.min_T_2
## 7.488573e-01 -1.303477e+00 -1.165197e+00
## S3.min_T_2 S4.min_T_2 S5.min_T_2
## 1.326384e+00 5.292843e-01 -2.263406e-01
## S7.min_T_2 S8.min_T_2 S9.min_T_2
## 1.751567e+00 -1.714401e-01 -1.955071e+00
## S10.15hs_T_2 S12.15hs_T_2 S13.15hs_T_2
## 1.754669e+00 -1.874793e+00 3.705275e+00
## S16.15hs_T_2 S17.15hs_T_2 S18.15hs_T_2
## 1.327204e+00 -4.052472e+00 2.915173e+00
## S19.15hs_T_2 S1.15hs_T_2 S2.15hs_T_2
## -4.434219e-01 2.121271e-04 1.967080e+00
## S4.15hs_T_2 S5.15hs_T_2 S8.15hs_T_2
## -2.483209e-01 -2.616027e-01 -2.394738e+00
## S9.15hs_T_2 S10.12hs_T_2 S11.12hs_T_2
## -2.185963e+00 -1.170769e+00 -1.162709e+00
## S12.12hs_T_2 S14.12hs_T_2 S15.12hs_T_2
## -4.019067e+00 -1.430467e+00 2.992758e+00
## S16.12hs_T_2 S17.12hs_T_2 S1.12hs_T_2
## 6.018859e-02 2.892387e-02 1.021939e-03
## S20.12hs_T_2 S2.12hs_T_2 S3.12hs_T_2
## -1.665547e-01 2.281066e+00 -1.179036e+00
## S5.12hs_T_2 S9.12hs_T_2 S10.18hs_T_2
## 1.899514e+00 1.772609e+00 -2.257490e+00
## S11.18hs_T_2 S14.18hs_T_2 S16.18hs_T_2
## 1.722703e-01 2.847069e+00 -4.668832e-01
## S17.18hs_T_2 S18.18hs_T_2 S1.18hs_T_2
## 5.331436e+00 -2.214939e+00 -1.635838e+00
## S2.18hs_T_2 S3.18hs_T_2 S4.18hs_T_2
## 3.916334e-03 -4.211911e+00 -9.546367e-01
## S6.18hs_T_2 S7.18hs_T_2 S8.18hs_T_2
## 1.517802e+00 2.205145e+00 -1.381755e+00
## S9.18hs_T_2 Est.humedad_min_T_2 Est.humedad_med_T_2
## 6.728067e-01 -6.913002e-01 6.974798e-01
## S10.max_T_1 S11.max_T_1 S15.max_T_1
## 7.097960e-02 8.901099e-01 -8.767834e-01
## S18.max_T_1 S19.max_T_1 S20.max_T_1
## 7.310435e-01 -1.064140e+00 -7.684644e-01
## S2.max_T_1 S3.max_T_1 S4.max_T_1
## 1.307035e+00 -6.394689e-01 1.744013e+00
## S7.max_T_1 S8.max_T_1 S9.max_T_1
## -2.040208e+00 4.155467e-01 2.767618e-02
## S10.media_T_1 S13.media_T_1 S15.media_T_1
## 2.135059e+00 -1.911681e+00 7.548776e+00
## S16.media_T_1 S18.media_T_1 S20.media_T_1
## -5.922036e-01 -8.149592e-01 -1.197683e+01
## S2.media_T_1 S3.media_T_1 S4.media_T_1
## -1.153338e+00 7.067426e+00 1.290660e+00
## S5.media_T_1 S6.media_T_1 S7.media_T_1
## -1.266032e+01 1.042802e+01 -9.616918e+00
## S8.media_T_1 S10.min_T_1 S11.min_T_1
## 1.094249e+01 4.975521e-01 1.377920e+00
## S12.min_T_1 S13.min_T_1 S14.min_T_1
## 1.673923e+00 -2.768251e-01 -1.158382e+00
## S16.min_T_1 S18.min_T_1 S19.min_T_1
## -2.343701e-01 9.048998e-01 -1.450892e+00
## S20.min_T_1 S2.min_T_1 S3.min_T_1
## -1.848708e+00 -2.794960e-02 9.229408e-01
## S4.min_T_1 S5.min_T_1 S6.min_T_1
## -7.203847e-01 -1.447147e+00 1.545076e-01
## S7.min_T_1 S8.min_T_1 S9.min_T_1
## 1.395041e+00 6.205984e-01 -3.164917e-01
## S10.15hs_T_1 S12.15hs_T_1 S13.15hs_T_1
## -1.201957e+00 6.226618e-01 -1.291515e+00
## S14.15hs_T_1 S17.15hs_T_1 S19.15hs_T_1
## 5.456820e-02 -1.016139e+00 2.533176e+00
## S1.15hs_T_1 S20.15hs_T_1 S3.15hs_T_1
## 2.255554e+00 2.814257e+00 -2.560966e-01
## S4.15hs_T_1 S8.15hs_T_1 S9.15hs_T_1
## -2.122764e+00 -1.710330e+00 -3.575930e-01
## S10.12hs_T_1 S13.12hs_T_1 S14.12hs_T_1
## 9.598556e-01 -7.810482e-01 -3.383353e-01
## S15.12hs_T_1 S16.12hs_T_1 S17.12hs_T_1
## -2.385824e+00 2.217533e-01 -9.434283e-01
## S19.12hs_T_1 S1.12hs_T_1 S20.12hs_T_1
## 1.690749e+00 -1.582805e+00 -1.852633e-01
## S2.12hs_T_1 S3.12hs_T_1 S4.12hs_T_1
## 4.133072e-01 3.924911e-02 3.880601e-01
## S5.12hs_T_1 S6.12hs_T_1 S7.12hs_T_1
## 8.863513e-01 -1.072475e+00 3.126313e+00
## S8.12hs_T_1 S9.12hs_T_1 S10.18hs_T_1
## -3.486113e-01 7.525553e-02 -3.456275e+00
## S11.18hs_T_1 S12.18hs_T_1 S13.18hs_T_1
## 2.087210e-01 7.757468e-01 5.481253e+00
## S14.18hs_T_1 S15.18hs_T_1 S16.18hs_T_1
## -1.513887e+00 -5.691082e-01 -6.034730e-01
## S17.18hs_T_1 S18.18hs_T_1 S19.18hs_T_1
## -1.777185e+00 5.213976e-01 9.920481e-01
## S1.18hs_T_1 S2.18hs_T_1 S3.18hs_T_1
## 8.461088e-02 1.403883e+00 2.367659e+00
## S5.18hs_T_1 S6.18hs_T_1 S7.18hs_T_1
## -1.260644e+00 -1.303443e+00 -1.167553e+00
## Est.temp_min_T_1 Est.temp_max_T_1 Est.temp_med_T_1
## -2.497383e+00 -3.180808e+00 5.735068e+00
## Standard deviation of the residuals: 4.3459e-08
##
## $S11.min_t
##
## Parameters of node S11.min_t (Gaussian distribution)
##
## Conditional density: S11.min_t | S10.max_T_2 + S11.max_T_2 + S12.max_T_2 + S13.max_T_2 + S14.max_T_2 + S16.max_T_2 + S17.max_T_2 + S18.max_T_2 + S19.max_T_2 + S20.max_T_2 + S2.max_T_2 + S5.max_T_2 + S6.max_T_2 + S7.max_T_2 + S9.max_T_2 + S10.media_T_2 + S11.media_T_2 + S12.media_T_2 + S14.media_T_2 + S17.media_T_2 + S18.media_T_2 + S19.media_T_2 + S3.media_T_2 + S4.media_T_2 + S5.media_T_2 + S6.media_T_2 + S7.media_T_2 + S10.min_T_2 + S11.min_T_2 + S12.min_T_2 + S13.min_T_2 + S14.min_T_2 + S15.min_T_2 + S16.min_T_2 + S17.min_T_2 + S18.min_T_2 + S1.min_T_2 + S20.min_T_2 + S2.min_T_2 + S4.min_T_2 + S6.min_T_2 + S7.min_T_2 + S9.min_T_2 + S10.15hs_T_2 + S11.15hs_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S16.15hs_T_2 + S18.15hs_T_2 + S19.15hs_T_2 + S1.15hs_T_2 + S3.15hs_T_2 + S4.15hs_T_2 + S5.15hs_T_2 + S7.15hs_T_2 + S9.15hs_T_2 + S11.12hs_T_2 + S12.12hs_T_2 + S14.12hs_T_2 + S18.12hs_T_2 + S19.12hs_T_2 + S1.12hs_T_2 + S2.12hs_T_2 + S3.12hs_T_2 + S7.12hs_T_2 + S8.12hs_T_2 + S9.12hs_T_2 + S10.18hs_T_2 + S11.18hs_T_2 + S12.18hs_T_2 + S13.18hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S17.18hs_T_2 + S18.18hs_T_2 + S19.18hs_T_2 + S1.18hs_T_2 + S4.18hs_T_2 + S5.18hs_T_2 + S8.18hs_T_2 + S10.max_T_1 + S11.max_T_1 + S12.max_T_1 + S14.max_T_1 + S15.max_T_1 + S17.max_T_1 + S18.max_T_1 + S19.max_T_1 + S1.max_T_1 + S20.max_T_1 + S2.max_T_1 + S3.max_T_1 + S4.max_T_1 + S5.max_T_1 + S6.max_T_1 + S7.max_T_1 + S8.max_T_1 + S9.max_T_1 + S10.media_T_1 + S11.media_T_1 + S12.media_T_1 + S14.media_T_1 + S16.media_T_1 + S17.media_T_1 + S18.media_T_1 + S1.media_T_1 + S20.media_T_1 + S2.media_T_1 + S3.media_T_1 + S4.media_T_1 + S5.media_T_1 + S6.media_T_1 + S7.media_T_1 + S8.media_T_1 + S9.media_T_1 + S10.min_T_1 + S11.min_T_1 + S12.min_T_1 + S13.min_T_1 + S15.min_T_1 + S16.min_T_1 + S18.min_T_1 + S19.min_T_1 + S1.min_T_1 + S20.min_T_1 + S2.min_T_1 + S3.min_T_1 + S4.min_T_1 + S6.min_T_1 + S7.min_T_1 + S8.min_T_1 + S10.15hs_T_1 + S11.15hs_T_1 + S12.15hs_T_1 + S13.15hs_T_1 + S14.15hs_T_1 + S16.15hs_T_1 + S18.15hs_T_1 + S19.15hs_T_1 + S1.15hs_T_1 + S2.15hs_T_1 + S4.15hs_T_1 + S6.15hs_T_1 + S11.12hs_T_1 + S12.12hs_T_1 + S14.12hs_T_1 + S16.12hs_T_1 + S17.12hs_T_1 + S18.12hs_T_1 + S1.12hs_T_1 + S20.12hs_T_1 + S2.12hs_T_1 + S3.12hs_T_1 + S4.12hs_T_1 + S5.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S11.18hs_T_1 + S12.18hs_T_1 + S13.18hs_T_1 + S14.18hs_T_1 + S16.18hs_T_1 + S18.18hs_T_1 + S19.18hs_T_1 + S1.18hs_T_1 + S20.18hs_T_1 + S4.18hs_T_1 + S6.18hs_T_1 + S7.18hs_T_1 + S8.18hs_T_1 + Est.humedad_med_T_1 + Est.humedad_max_T_1 + Est.temp_min_T_1 + Est.temp_max_T_1 + Est.temp_med_T_1
## Coefficients:
## (Intercept) S10.max_T_2 S11.max_T_2
## -1.738243e+00 -1.014839e+00 7.342805e-01
## S12.max_T_2 S13.max_T_2 S14.max_T_2
## -8.711034e-01 1.817346e+00 1.313515e+00
## S16.max_T_2 S17.max_T_2 S18.max_T_2
## 3.200733e-01 -5.512874e-02 4.355152e-01
## S19.max_T_2 S20.max_T_2 S2.max_T_2
## -2.314816e+00 2.002884e+00 -2.479080e+00
## S5.max_T_2 S6.max_T_2 S7.max_T_2
## -4.025652e-01 -4.621811e-01 9.520627e-01
## S9.max_T_2 S10.media_T_2 S11.media_T_2
## -1.728177e-03 1.563723e-01 -4.305042e+00
## S12.media_T_2 S14.media_T_2 S17.media_T_2
## -5.568409e+00 -7.820218e+00 -7.825721e+00
## S18.media_T_2 S19.media_T_2 S3.media_T_2
## -5.190435e+00 1.276847e+00 -2.139004e+00
## S4.media_T_2 S5.media_T_2 S6.media_T_2
## 8.533891e+00 7.062795e+00 -1.750561e+00
## S7.media_T_2 S10.min_T_2 S11.min_T_2
## 1.700576e+01 6.019373e+00 -2.024098e-01
## S12.min_T_2 S13.min_T_2 S14.min_T_2
## 5.855287e-01 1.591139e+00 -2.142539e+00
## S15.min_T_2 S16.min_T_2 S17.min_T_2
## -1.107563e+00 -1.627378e+00 1.337846e+00
## S18.min_T_2 S1.min_T_2 S20.min_T_2
## 6.573454e-01 -1.135246e+00 3.489768e+00
## S2.min_T_2 S4.min_T_2 S6.min_T_2
## 8.646560e-02 4.770807e-01 -1.159013e+00
## S7.min_T_2 S9.min_T_2 S10.15hs_T_2
## -2.268547e-01 -6.231948e+00 -9.173056e-01
## S11.15hs_T_2 S12.15hs_T_2 S13.15hs_T_2
## 6.550950e-01 -1.313716e-01 1.230692e+00
## S16.15hs_T_2 S18.15hs_T_2 S19.15hs_T_2
## 1.040678e-02 2.775345e+00 4.035661e-01
## S1.15hs_T_2 S3.15hs_T_2 S4.15hs_T_2
## -2.516585e-01 5.988371e-01 -5.733796e-01
## S5.15hs_T_2 S7.15hs_T_2 S9.15hs_T_2
## -1.304159e+00 -4.836894e-01 -1.691814e+00
## S11.12hs_T_2 S12.12hs_T_2 S14.12hs_T_2
## -1.055898e-01 -7.459898e-01 1.889662e+00
## S18.12hs_T_2 S19.12hs_T_2 S1.12hs_T_2
## -1.028987e+00 -1.272194e+00 1.870170e-02
## S2.12hs_T_2 S3.12hs_T_2 S7.12hs_T_2
## 1.462965e+00 -1.226063e+00 2.948588e-02
## S8.12hs_T_2 S9.12hs_T_2 S10.18hs_T_2
## -1.075400e+00 1.652402e+00 -1.633713e+00
## S11.18hs_T_2 S12.18hs_T_2 S13.18hs_T_2
## -3.920731e+00 2.821327e-01 1.868319e+00
## S14.18hs_T_2 S15.18hs_T_2 S17.18hs_T_2
## 2.047133e+00 8.604182e-02 2.980362e+00
## S18.18hs_T_2 S19.18hs_T_2 S1.18hs_T_2
## -3.513452e-02 1.572899e+00 -2.350037e+00
## S4.18hs_T_2 S5.18hs_T_2 S8.18hs_T_2
## -2.175785e-01 -1.242167e+00 4.812803e-01
## S10.max_T_1 S11.max_T_1 S12.max_T_1
## -7.228915e-02 2.759456e+00 -7.874749e-01
## S14.max_T_1 S15.max_T_1 S17.max_T_1
## 3.334794e-01 -1.611198e-05 -7.655027e-01
## S18.max_T_1 S19.max_T_1 S1.max_T_1
## -5.437183e-01 -1.294027e+00 -9.016387e-01
## S20.max_T_1 S2.max_T_1 S3.max_T_1
## -8.738116e-01 2.968239e+00 -1.579269e-01
## S4.max_T_1 S5.max_T_1 S6.max_T_1
## 1.107767e+00 8.654348e-01 -5.827437e-01
## S7.max_T_1 S8.max_T_1 S9.max_T_1
## -8.166805e-01 -1.015095e-01 -1.130616e+00
## S10.media_T_1 S11.media_T_1 S12.media_T_1
## 3.425700e+00 6.904955e+00 2.325948e+00
## S14.media_T_1 S16.media_T_1 S17.media_T_1
## -1.121338e+01 9.739560e+00 -7.453715e+00
## S18.media_T_1 S1.media_T_1 S20.media_T_1
## 7.589217e+00 1.080365e+01 -1.160990e+01
## S2.media_T_1 S3.media_T_1 S4.media_T_1
## 7.408546e-01 3.123322e+00 9.140125e+00
## S5.media_T_1 S6.media_T_1 S7.media_T_1
## -2.176619e+01 5.670674e+00 -1.519522e+01
## S8.media_T_1 S9.media_T_1 S10.min_T_1
## 9.925619e+00 -8.647167e-02 2.563181e+00
## S11.min_T_1 S12.min_T_1 S13.min_T_1
## 1.975260e+00 5.312512e+00 -6.591779e-01
## S15.min_T_1 S16.min_T_1 S18.min_T_1
## 4.706621e-01 -5.593488e+00 1.009124e+00
## S19.min_T_1 S1.min_T_1 S20.min_T_1
## 6.904300e-01 -1.446005e+00 1.399629e-01
## S2.min_T_1 S3.min_T_1 S4.min_T_1
## 2.415946e-02 9.127390e-01 -3.415675e+00
## S6.min_T_1 S7.min_T_1 S8.min_T_1
## 1.948995e-01 -5.752475e-01 -1.735761e+00
## S10.15hs_T_1 S11.15hs_T_1 S12.15hs_T_1
## 5.854199e-01 -2.048761e+00 1.644569e+00
## S13.15hs_T_1 S14.15hs_T_1 S16.15hs_T_1
## -1.801642e+00 1.462902e+00 -2.573364e-01
## S18.15hs_T_1 S19.15hs_T_1 S1.15hs_T_1
## -2.794149e-01 1.358609e-01 7.249650e-02
## S2.15hs_T_1 S4.15hs_T_1 S6.15hs_T_1
## 3.207217e-01 6.277647e-02 2.310754e-01
## S11.12hs_T_1 S12.12hs_T_1 S14.12hs_T_1
## -1.064246e+00 -1.970748e-01 6.506463e-01
## S16.12hs_T_1 S17.12hs_T_1 S18.12hs_T_1
## 2.976612e-02 1.753002e-01 -2.113678e+00
## S1.12hs_T_1 S20.12hs_T_1 S2.12hs_T_1
## -1.870365e+00 -1.296400e+00 7.817214e-01
## S3.12hs_T_1 S4.12hs_T_1 S5.12hs_T_1
## 2.517279e+00 -5.544944e-01 1.676176e+00
## S6.12hs_T_1 S7.12hs_T_1 S8.12hs_T_1
## -1.631292e+00 3.148447e+00 -7.015881e-01
## S11.18hs_T_1 S12.18hs_T_1 S13.18hs_T_1
## -3.213980e-01 -1.437926e+00 2.365534e+00
## S14.18hs_T_1 S16.18hs_T_1 S18.18hs_T_1
## 7.874787e-03 -4.430287e-01 3.191751e-01
## S19.18hs_T_1 S1.18hs_T_1 S20.18hs_T_1
## 2.543483e-02 -4.492501e-01 1.755125e+00
## S4.18hs_T_1 S6.18hs_T_1 S7.18hs_T_1
## -1.791635e+00 -4.978840e-01 -9.925418e-01
## S8.18hs_T_1 Est.humedad_med_T_1 Est.humedad_max_T_1
## 1.171251e+00 5.439482e-01 -5.768082e-01
## Est.temp_min_T_1 Est.temp_max_T_1 Est.temp_med_T_1
## 5.165432e+00 6.402256e+00 -1.134336e+01
## Standard deviation of the residuals: 5.859015e-08
##
## $S12.min_t
##
## Parameters of node S12.min_t (Gaussian distribution)
##
## Conditional density: S12.min_t | S11.max_T_2 + S12.max_T_2 + S16.max_T_2 + S19.max_T_2 + S8.max_T_2 + S12.media_T_2 + S15.media_T_2 + S20.media_T_2 + S3.media_T_2 + S4.media_T_2 + S6.media_T_2 + S10.min_T_2 + S12.min_T_2 + S16.min_T_2 + S9.min_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S17.15hs_T_2 + S5.15hs_T_2 + S6.15hs_T_2 + S12.12hs_T_2 + S5.12hs_T_2 + S9.12hs_T_2 + S10.18hs_T_2 + S12.18hs_T_2 + S14.18hs_T_2 + S17.18hs_T_2 + S1.18hs_T_2 + S4.18hs_T_2 + S7.18hs_T_2 + Est.temp_min_T_2 + S12.max_T_1 + S14.max_T_1 + S17.max_T_1 + S1.max_T_1 + S2.max_T_1 + S3.max_T_1 + S9.max_T_1 + S12.media_T_1 + S20.media_T_1 + S5.media_T_1 + S6.media_T_1 + S8.media_T_1 + S12.min_T_1 + S14.min_T_1 + S17.min_T_1 + S18.min_T_1 + S20.min_T_1 + S6.min_T_1 + S8.min_T_1 + S12.15hs_T_1 + S1.15hs_T_1 + S2.15hs_T_1 + S3.15hs_T_1 + S12.12hs_T_1 + S16.12hs_T_1 + S18.12hs_T_1 + S4.12hs_T_1 + S6.12hs_T_1 + S12.18hs_T_1 + S3.18hs_T_1 + S4.18hs_T_1 + Est.humedad_min_T_1
## Coefficients:
## (Intercept) S11.max_T_2 S12.max_T_2
## -9.18150442 -1.15467113 0.05485633
## S16.max_T_2 S19.max_T_2 S8.max_T_2
## 0.33177082 0.28527642 0.49808231
## S12.media_T_2 S15.media_T_2 S20.media_T_2
## -3.90356340 -2.12867226 4.48309416
## S3.media_T_2 S4.media_T_2 S6.media_T_2
## -3.28908466 2.47472295 2.35624610
## S10.min_T_2 S12.min_T_2 S16.min_T_2
## 1.10301851 1.74615219 -1.51313603
## S9.min_T_2 S12.15hs_T_2 S13.15hs_T_2
## -1.23900300 0.32837924 1.65627917
## S17.15hs_T_2 S5.15hs_T_2 S6.15hs_T_2
## -1.42318435 -1.73674531 1.26190499
## S12.12hs_T_2 S5.12hs_T_2 S9.12hs_T_2
## -1.35653646 0.58986811 0.55622292
## S10.18hs_T_2 S12.18hs_T_2 S14.18hs_T_2
## -3.26508654 0.93664249 2.54147391
## S17.18hs_T_2 S1.18hs_T_2 S4.18hs_T_2
## 1.24967644 -1.13697260 -0.75351513
## S7.18hs_T_2 Est.temp_min_T_2 S12.max_T_1
## 0.55644770 0.15076064 0.62265238
## S14.max_T_1 S17.max_T_1 S1.max_T_1
## 0.94789044 -1.51890875 -0.58247046
## S2.max_T_1 S3.max_T_1 S9.max_T_1
## 1.80088504 -0.77014161 -0.90077286
## S12.media_T_1 S20.media_T_1 S5.media_T_1
## -2.52617824 -1.75180436 -3.34002604
## S6.media_T_1 S8.media_T_1 S12.min_T_1
## 4.26914448 3.62811746 3.08581304
## S14.min_T_1 S17.min_T_1 S18.min_T_1
## -1.65383872 -0.67334210 0.98403181
## S20.min_T_1 S6.min_T_1 S8.min_T_1
## -0.82528896 2.04284743 -2.71578841
## S12.15hs_T_1 S1.15hs_T_1 S2.15hs_T_1
## -1.40837595 2.12392864 -1.90512105
## S3.15hs_T_1 S12.12hs_T_1 S16.12hs_T_1
## 1.57088001 0.38819188 -0.64558354
## S18.12hs_T_1 S4.12hs_T_1 S6.12hs_T_1
## 0.55810595 1.25913728 -1.39643571
## S12.18hs_T_1 S3.18hs_T_1 S4.18hs_T_1
## 1.47413314 -0.97169918 -0.47546478
## Est.humedad_min_T_1
## 0.05166132
## Standard deviation of the residuals: 0.9003216
##
## $S13.min_t
##
## Parameters of node S13.min_t (Gaussian distribution)
##
## Conditional density: S13.min_t | S10.max_T_2 + S11.max_T_2 + S12.max_T_2 + S13.max_T_2 + S14.max_T_2 + S15.max_T_2 + S17.max_T_2 + S18.max_T_2 + S20.max_T_2 + S2.max_T_2 + S5.max_T_2 + S8.max_T_2 + S9.max_T_2 + S10.media_T_2 + S11.media_T_2 + S12.media_T_2 + S13.media_T_2 + S14.media_T_2 + S15.media_T_2 + S17.media_T_2 + S18.media_T_2 + S19.media_T_2 + S1.media_T_2 + S3.media_T_2 + S6.media_T_2 + S7.media_T_2 + S9.media_T_2 + S10.min_T_2 + S11.min_T_2 + S12.min_T_2 + S13.min_T_2 + S14.min_T_2 + S15.min_T_2 + S16.min_T_2 + S17.min_T_2 + S18.min_T_2 + S19.min_T_2 + S20.min_T_2 + S4.min_T_2 + S8.min_T_2 + S9.min_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S14.15hs_T_2 + S16.15hs_T_2 + S17.15hs_T_2 + S18.15hs_T_2 + S19.15hs_T_2 + S20.15hs_T_2 + S2.15hs_T_2 + S4.15hs_T_2 + S5.15hs_T_2 + S7.15hs_T_2 + S8.15hs_T_2 + S9.15hs_T_2 + S11.12hs_T_2 + S12.12hs_T_2 + S13.12hs_T_2 + S15.12hs_T_2 + S17.12hs_T_2 + S18.12hs_T_2 + S19.12hs_T_2 + S3.12hs_T_2 + S4.12hs_T_2 + S5.12hs_T_2 + S6.12hs_T_2 + S7.12hs_T_2 + S8.12hs_T_2 + S9.12hs_T_2 + S10.18hs_T_2 + S11.18hs_T_2 + S12.18hs_T_2 + S13.18hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S17.18hs_T_2 + S18.18hs_T_2 + S1.18hs_T_2 + S20.18hs_T_2 + S2.18hs_T_2 + S3.18hs_T_2 + S4.18hs_T_2 + S5.18hs_T_2 + S6.18hs_T_2 + S9.18hs_T_2 + Est.humedad_min_T_2 + Est.humedad_max_T_2 + S10.max_T_1 + S13.max_T_1 + S14.max_T_1 + S15.max_T_1 + S17.max_T_1 + S19.max_T_1 + S1.max_T_1 + S2.max_T_1 + S3.max_T_1 + S4.max_T_1 + S5.max_T_1 + S6.max_T_1 + S8.max_T_1 + S10.media_T_1 + S12.media_T_1 + S13.media_T_1 + S16.media_T_1 + S17.media_T_1 + S18.media_T_1 + S19.media_T_1 + S1.media_T_1 + S20.media_T_1 + S2.media_T_1 + S3.media_T_1 + S5.media_T_1 + S6.media_T_1 + S7.media_T_1 + S8.media_T_1 + S9.media_T_1 + S11.min_T_1 + S12.min_T_1 + S13.min_T_1 + S16.min_T_1 + S17.min_T_1 + S18.min_T_1 + S19.min_T_1 + S1.min_T_1 + S2.min_T_1 + S3.min_T_1 + S4.min_T_1 + S6.min_T_1 + S7.min_T_1 + S9.min_T_1 + S10.15hs_T_1 + S13.15hs_T_1 + S14.15hs_T_1 + S16.15hs_T_1 + S17.15hs_T_1 + S18.15hs_T_1 + S19.15hs_T_1 + S20.15hs_T_1 + S2.15hs_T_1 + S3.15hs_T_1 + S5.15hs_T_1 + S6.15hs_T_1 + S7.15hs_T_1 + S9.15hs_T_1 + S10.12hs_T_1 + S11.12hs_T_1 + S12.12hs_T_1 + S13.12hs_T_1 + S14.12hs_T_1 + S15.12hs_T_1 + S16.12hs_T_1 + S17.12hs_T_1 + S1.12hs_T_1 + S2.12hs_T_1 + S4.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S9.12hs_T_1 + S10.18hs_T_1 + S11.18hs_T_1 + S12.18hs_T_1 + S13.18hs_T_1 + S14.18hs_T_1 + S15.18hs_T_1 + S17.18hs_T_1 + S18.18hs_T_1 + S1.18hs_T_1 + S2.18hs_T_1 + S3.18hs_T_1 + S4.18hs_T_1 + S5.18hs_T_1 + S7.18hs_T_1 + S8.18hs_T_1 + S9.18hs_T_1 + Est.humedad_min_T_1
## Coefficients:
## (Intercept) S10.max_T_2 S11.max_T_2
## -3.626539582 -0.084718257 -0.393354853
## S12.max_T_2 S13.max_T_2 S14.max_T_2
## -0.892432870 1.129267532 0.989821172
## S15.max_T_2 S17.max_T_2 S18.max_T_2
## -0.143010424 -0.236339715 -0.280754460
## S20.max_T_2 S2.max_T_2 S5.max_T_2
## 0.326524268 -2.256554377 0.311457139
## S8.max_T_2 S9.max_T_2 S10.media_T_2
## 0.805654911 0.598945378 -3.580799816
## S11.media_T_2 S12.media_T_2 S13.media_T_2
## 0.299856858 3.440992541 -1.404133091
## S14.media_T_2 S15.media_T_2 S17.media_T_2
## 0.001027008 0.166634654 -9.698886785
## S18.media_T_2 S19.media_T_2 S1.media_T_2
## 1.929581760 -8.494521637 5.061406170
## S3.media_T_2 S6.media_T_2 S7.media_T_2
## -0.334665275 -0.146286285 14.405704077
## S9.media_T_2 S10.min_T_2 S11.min_T_2
## -1.853748793 0.326956023 1.436842197
## S12.min_T_2 S13.min_T_2 S14.min_T_2
## 1.756537934 -1.073623742 -0.897526125
## S15.min_T_2 S16.min_T_2 S17.min_T_2
## 0.811389854 0.561762799 1.746360095
## S18.min_T_2 S19.min_T_2 S20.min_T_2
## -1.261204849 -0.003864289 -0.131064011
## S4.min_T_2 S8.min_T_2 S9.min_T_2
## 1.883919470 -1.022107399 -3.682933082
## S12.15hs_T_2 S13.15hs_T_2 S14.15hs_T_2
## -4.426256187 4.891553991 -3.108707570
## S16.15hs_T_2 S17.15hs_T_2 S18.15hs_T_2
## 0.563659096 -1.056266804 3.347626316
## S19.15hs_T_2 S20.15hs_T_2 S2.15hs_T_2
## 0.920763344 -0.406352176 2.791383537
## S4.15hs_T_2 S5.15hs_T_2 S7.15hs_T_2
## 1.166667562 -2.397483395 -0.032811932
## S8.15hs_T_2 S9.15hs_T_2 S11.12hs_T_2
## -2.059035151 0.148400087 -0.375888156
## S12.12hs_T_2 S13.12hs_T_2 S15.12hs_T_2
## -0.277138266 -3.375287337 0.442353675
## S17.12hs_T_2 S18.12hs_T_2 S19.12hs_T_2
## 0.715033425 0.431378642 1.389758446
## S3.12hs_T_2 S4.12hs_T_2 S5.12hs_T_2
## -0.462460185 0.738574751 1.391521235
## S6.12hs_T_2 S7.12hs_T_2 S8.12hs_T_2
## -0.582105528 -1.316941087 1.282314919
## S9.12hs_T_2 S10.18hs_T_2 S11.18hs_T_2
## -0.226529231 -0.497194576 -2.105109227
## S12.18hs_T_2 S13.18hs_T_2 S14.18hs_T_2
## 1.600745824 -0.800706916 3.233771890
## S15.18hs_T_2 S17.18hs_T_2 S18.18hs_T_2
## 3.746183134 0.353544868 -2.114318026
## S1.18hs_T_2 S20.18hs_T_2 S2.18hs_T_2
## -3.781865599 2.537691957 1.790912547
## S3.18hs_T_2 S4.18hs_T_2 S5.18hs_T_2
## -2.583980091 -2.461958810 -1.116600941
## S6.18hs_T_2 S9.18hs_T_2 Est.humedad_min_T_2
## 1.480190491 0.659919841 -0.194474964
## Est.humedad_max_T_2 S10.max_T_1 S13.max_T_1
## 0.224834125 -0.849794410 0.515546849
## S14.max_T_1 S15.max_T_1 S17.max_T_1
## 0.381358558 -0.781008753 -1.060178764
## S19.max_T_1 S1.max_T_1 S2.max_T_1
## -1.038058222 -1.381626418 1.479041369
## S3.max_T_1 S4.max_T_1 S5.max_T_1
## 0.663553037 0.722143576 -0.310318032
## S6.max_T_1 S8.max_T_1 S10.media_T_1
## -2.184702713 3.359139816 0.621970637
## S12.media_T_1 S13.media_T_1 S16.media_T_1
## 0.227646106 4.316376224 2.737089415
## S17.media_T_1 S18.media_T_1 S19.media_T_1
## -1.969932845 1.825025200 4.053213223
## S1.media_T_1 S20.media_T_1 S2.media_T_1
## 5.888756290 -9.412133425 0.450617559
## S3.media_T_1 S5.media_T_1 S6.media_T_1
## -3.034416435 0.520328050 3.693436454
## S7.media_T_1 S8.media_T_1 S9.media_T_1
## -6.867662814 0.541109208 -3.073860141
## S11.min_T_1 S12.min_T_1 S13.min_T_1
## 1.705896461 5.920594096 0.337305929
## S16.min_T_1 S17.min_T_1 S18.min_T_1
## -5.148743815 -0.424924474 0.118551995
## S19.min_T_1 S1.min_T_1 S2.min_T_1
## -1.089914006 2.258639983 -0.970302872
## S3.min_T_1 S4.min_T_1 S6.min_T_1
## 1.390177667 -2.889110766 -0.659257493
## S7.min_T_1 S9.min_T_1 S10.15hs_T_1
## 0.001554127 -0.320166389 -3.383032052
## S13.15hs_T_1 S14.15hs_T_1 S16.15hs_T_1
## -2.082640929 -0.049288878 -1.453692530
## S17.15hs_T_1 S18.15hs_T_1 S19.15hs_T_1
## 0.092877390 2.091857820 -0.274256584
## S20.15hs_T_1 S2.15hs_T_1 S3.15hs_T_1
## 1.557460920 -0.755598013 1.753734685
## S5.15hs_T_1 S6.15hs_T_1 S7.15hs_T_1
## -0.358079086 1.191200601 0.930864609
## S9.15hs_T_1 S10.12hs_T_1 S11.12hs_T_1
## 1.657639255 0.989515920 -0.519699292
## S12.12hs_T_1 S13.12hs_T_1 S14.12hs_T_1
## -1.184202854 -0.971333619 0.769072515
## S15.12hs_T_1 S16.12hs_T_1 S17.12hs_T_1
## -0.014009255 -0.105884707 -1.592621317
## S1.12hs_T_1 S2.12hs_T_1 S4.12hs_T_1
## 0.657349860 -1.423662683 0.673829577
## S6.12hs_T_1 S7.12hs_T_1 S8.12hs_T_1
## -1.313903070 3.845082200 -0.265517020
## S9.12hs_T_1 S10.18hs_T_1 S11.18hs_T_1
## 0.325911696 -0.041734860 0.479982601
## S12.18hs_T_1 S13.18hs_T_1 S14.18hs_T_1
## 3.668690399 0.492213340 -1.521490816
## S15.18hs_T_1 S17.18hs_T_1 S18.18hs_T_1
## 2.124519692 -3.065337037 1.974137435
## S1.18hs_T_1 S2.18hs_T_1 S3.18hs_T_1
## -0.755710934 -0.489717917 -0.535099907
## S4.18hs_T_1 S5.18hs_T_1 S7.18hs_T_1
## 1.429296254 -3.156658442 -1.338883636
## S8.18hs_T_1 S9.18hs_T_1 Est.humedad_min_T_1
## -0.086183388 0.367752418 0.022393919
## Standard deviation of the residuals: 1.205142e-07
##
## $S14.min_t
##
## Parameters of node S14.min_t (Gaussian distribution)
##
## Conditional density: S14.min_t | S10.max_T_2 + S11.max_T_2 + S14.max_T_2 + S16.max_T_2 + S20.max_T_2 + S2.max_T_2 + S5.max_T_2 + S9.max_T_2 + S13.media_T_2 + S14.media_T_2 + S4.media_T_2 + S6.media_T_2 + S12.min_T_2 + S14.min_T_2 + S16.min_T_2 + S20.min_T_2 + S2.min_T_2 + S9.min_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S14.15hs_T_2 + S17.15hs_T_2 + S19.15hs_T_2 + S20.15hs_T_2 + S2.15hs_T_2 + S3.15hs_T_2 + S4.15hs_T_2 + S5.15hs_T_2 + S6.15hs_T_2 + S9.15hs_T_2 + S10.12hs_T_2 + S14.12hs_T_2 + S5.12hs_T_2 + S8.12hs_T_2 + S10.18hs_T_2 + S14.18hs_T_2 + S17.18hs_T_2 + S3.18hs_T_2 + S5.18hs_T_2 + S8.18hs_T_2 + S9.18hs_T_2 + Est.humedad_max_T_2 + S11.max_T_1 + S13.max_T_1 + S14.max_T_1 + S17.max_T_1 + S18.max_T_1 + S20.max_T_1 + S2.max_T_1 + S3.max_T_1 + S8.max_T_1 + S9.max_T_1 + S10.media_T_1 + S14.media_T_1 + S17.media_T_1 + S5.media_T_1 + S6.media_T_1 + S7.media_T_1 + S8.media_T_1 + S9.media_T_1 + S10.min_T_1 + S12.min_T_1 + S14.min_T_1 + S16.min_T_1 + S17.min_T_1 + S6.min_T_1 + S8.min_T_1 + S10.15hs_T_1 + S12.15hs_T_1 + S14.15hs_T_1 + S15.15hs_T_1 + S16.15hs_T_1 + S18.15hs_T_1 + S1.15hs_T_1 + S2.15hs_T_1 + S3.15hs_T_1 + S14.12hs_T_1 + S4.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S9.12hs_T_1 + S14.18hs_T_1 + Est.humedad_med_T_1 + Est.temp_min_T_1 + Est.temp_max_T_1 + Est.temp_med_T_1
## Coefficients:
## (Intercept) S10.max_T_2 S11.max_T_2
## -3.71992097 -1.58386035 -0.89716905
## S14.max_T_2 S16.max_T_2 S20.max_T_2
## 1.09829098 0.54997990 0.96339757
## S2.max_T_2 S5.max_T_2 S9.max_T_2
## -0.78299204 -0.68965928 1.59854682
## S13.media_T_2 S14.media_T_2 S4.media_T_2
## -4.04827695 -2.15812221 4.01483974
## S6.media_T_2 S12.min_T_2 S14.min_T_2
## 2.02147327 1.41270584 2.21237580
## S16.min_T_2 S20.min_T_2 S2.min_T_2
## -1.08239795 1.09931278 -1.91319237
## S9.min_T_2 S12.15hs_T_2 S13.15hs_T_2
## -1.60788407 -1.10857770 3.14094455
## S14.15hs_T_2 S17.15hs_T_2 S19.15hs_T_2
## -0.77993929 -2.32937012 0.55641635
## S20.15hs_T_2 S2.15hs_T_2 S3.15hs_T_2
## -0.94584278 1.41256839 -0.38942502
## S4.15hs_T_2 S5.15hs_T_2 S6.15hs_T_2
## 1.34410873 -1.00931674 0.86399457
## S9.15hs_T_2 S10.12hs_T_2 S14.12hs_T_2
## -1.06322876 -0.40517253 -0.91530917
## S5.12hs_T_2 S8.12hs_T_2 S10.18hs_T_2
## 0.38417251 0.92954054 -2.32517537
## S14.18hs_T_2 S17.18hs_T_2 S3.18hs_T_2
## 3.19863990 1.74434830 -0.82536703
## S5.18hs_T_2 S8.18hs_T_2 S9.18hs_T_2
## -1.94629532 0.91145923 -0.66261641
## Est.humedad_max_T_2 S11.max_T_1 S13.max_T_1
## -0.03589482 0.81680842 -0.78230465
## S14.max_T_1 S17.max_T_1 S18.max_T_1
## 1.07072432 -0.95002479 -0.66561878
## S20.max_T_1 S2.max_T_1 S3.max_T_1
## -0.95812957 1.88930507 -0.80147525
## S8.max_T_1 S9.max_T_1 S10.media_T_1
## 0.84092285 -0.80730628 6.17227747
## S14.media_T_1 S17.media_T_1 S5.media_T_1
## -1.83898946 -2.05093265 -5.17547440
## S6.media_T_1 S7.media_T_1 S8.media_T_1
## 5.74385059 -2.06869707 5.00106000
## S9.media_T_1 S10.min_T_1 S12.min_T_1
## -5.12192031 1.19435345 3.29686557
## S14.min_T_1 S16.min_T_1 S17.min_T_1
## -0.78241877 -0.93197693 -0.58721561
## S6.min_T_1 S8.min_T_1 S10.15hs_T_1
## 0.82763842 -2.79103627 -1.59840362
## S12.15hs_T_1 S14.15hs_T_1 S15.15hs_T_1
## -0.81505194 0.60938493 -0.58903372
## S16.15hs_T_1 S18.15hs_T_1 S1.15hs_T_1
## -0.63113867 1.44759399 0.85212620
## S2.15hs_T_1 S3.15hs_T_1 S14.12hs_T_1
## -0.57766244 1.97457616 -0.40095850
## S4.12hs_T_1 S6.12hs_T_1 S7.12hs_T_1
## 1.48516977 -2.12446676 1.10116404
## S8.12hs_T_1 S9.12hs_T_1 S14.18hs_T_1
## -0.84021147 0.56627335 -0.03355250
## Est.humedad_med_T_1 Est.temp_min_T_1 Est.temp_max_T_1
## 0.04382743 5.87745038 3.97705324
## Est.temp_med_T_1
## -9.77454231
## Standard deviation of the residuals: 0.603303
##
## $S15.min_t
##
## Parameters of node S15.min_t (Gaussian distribution)
##
## Conditional density: S15.min_t | S10.max_T_2 + S11.max_T_2 + S12.max_T_2 + S14.max_T_2 + S15.max_T_2 + S18.max_T_2 + S1.max_T_2 + S20.max_T_2 + S2.max_T_2 + S3.max_T_2 + S5.max_T_2 + S7.max_T_2 + S8.max_T_2 + S9.max_T_2 + S10.media_T_2 + S12.media_T_2 + S13.media_T_2 + S15.media_T_2 + S16.media_T_2 + S17.media_T_2 + S18.media_T_2 + S20.media_T_2 + S4.media_T_2 + S5.media_T_2 + S6.media_T_2 + S9.media_T_2 + S10.min_T_2 + S11.min_T_2 + S12.min_T_2 + S15.min_T_2 + S17.min_T_2 + S18.min_T_2 + S1.min_T_2 + S20.min_T_2 + S2.min_T_2 + S5.min_T_2 + S6.min_T_2 + S8.min_T_2 + S9.min_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S14.15hs_T_2 + S15.15hs_T_2 + S16.15hs_T_2 + S17.15hs_T_2 + S18.15hs_T_2 + S2.15hs_T_2 + S3.15hs_T_2 + S4.15hs_T_2 + S5.15hs_T_2 + S6.15hs_T_2 + S7.15hs_T_2 + S9.15hs_T_2 + S10.12hs_T_2 + S11.12hs_T_2 + S12.12hs_T_2 + S14.12hs_T_2 + S15.12hs_T_2 + S16.12hs_T_2 + S17.12hs_T_2 + S18.12hs_T_2 + S1.12hs_T_2 + S20.12hs_T_2 + S2.12hs_T_2 + S3.12hs_T_2 + S5.12hs_T_2 + S7.12hs_T_2 + S8.12hs_T_2 + S10.18hs_T_2 + S11.18hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S16.18hs_T_2 + S18.18hs_T_2 + S1.18hs_T_2 + S20.18hs_T_2 + S2.18hs_T_2 + S3.18hs_T_2 + S4.18hs_T_2 + S5.18hs_T_2 + S6.18hs_T_2 + S7.18hs_T_2 + S8.18hs_T_2 + S9.18hs_T_2 + Est.humedad_med_T_2 + Est.temp_max_T_2 + S10.max_T_1 + S11.max_T_1 + S14.max_T_1 + S15.max_T_1 + S16.max_T_1 + S17.max_T_1 + S19.max_T_1 + S1.max_T_1 + S20.max_T_1 + S2.max_T_1 + S3.max_T_1 + S4.max_T_1 + S7.max_T_1 + S8.max_T_1 + S9.max_T_1 + S10.media_T_1 + S11.media_T_1 + S12.media_T_1 + S13.media_T_1 + S14.media_T_1 + S15.media_T_1 + S16.media_T_1 + S18.media_T_1 + S1.media_T_1 + S2.media_T_1 + S5.media_T_1 + S6.media_T_1 + S7.media_T_1 + S8.media_T_1 + S9.media_T_1 + S12.min_T_1 + S13.min_T_1 + S14.min_T_1 + S15.min_T_1 + S17.min_T_1 + S18.min_T_1 + S19.min_T_1 + S1.min_T_1 + S2.min_T_1 + S3.min_T_1 + S4.min_T_1 + S5.min_T_1 + S6.min_T_1 + S8.min_T_1 + S10.15hs_T_1 + S11.15hs_T_1 + S12.15hs_T_1 + S15.15hs_T_1 + S16.15hs_T_1 + S18.15hs_T_1 + S19.15hs_T_1 + S1.15hs_T_1 + S20.15hs_T_1 + S2.15hs_T_1 + S3.15hs_T_1 + S4.15hs_T_1 + S5.15hs_T_1 + S6.15hs_T_1 + S7.15hs_T_1 + S9.15hs_T_1 + S10.12hs_T_1 + S11.12hs_T_1 + S12.12hs_T_1 + S15.12hs_T_1 + S16.12hs_T_1 + S18.12hs_T_1 + S19.12hs_T_1 + S1.12hs_T_1 + S20.12hs_T_1 + S2.12hs_T_1 + S3.12hs_T_1 + S4.12hs_T_1 + S5.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S12.18hs_T_1 + S13.18hs_T_1 + S14.18hs_T_1 + S15.18hs_T_1 + S1.18hs_T_1 + S3.18hs_T_1 + S5.18hs_T_1 + S6.18hs_T_1 + S7.18hs_T_1 + S8.18hs_T_1 + S9.18hs_T_1 + Est.humedad_min_T_1 + Est.humedad_med_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S10.max_T_2 S11.max_T_2
## -1.474679e+01 -1.009689e+00 9.418036e-04
## S12.max_T_2 S14.max_T_2 S15.max_T_2
## 6.801079e-01 1.406029e+00 -1.370604e-01
## S18.max_T_2 S1.max_T_2 S20.max_T_2
## -1.901526e+00 1.034725e+00 1.789711e+00
## S2.max_T_2 S3.max_T_2 S5.max_T_2
## -9.289013e-01 1.407867e+00 -3.475552e+00
## S7.max_T_2 S8.max_T_2 S9.max_T_2
## 4.831892e-01 3.565917e-01 8.720405e-01
## S10.media_T_2 S12.media_T_2 S13.media_T_2
## -4.610991e+00 -6.212379e-01 -6.103619e+00
## S15.media_T_2 S16.media_T_2 S17.media_T_2
## -4.718829e+00 3.939744e-04 1.218387e+00
## S18.media_T_2 S20.media_T_2 S4.media_T_2
## 3.362876e+00 -4.564251e+00 8.591813e+00
## S5.media_T_2 S6.media_T_2 S9.media_T_2
## -2.027035e+00 6.225805e-01 8.199906e+00
## S10.min_T_2 S11.min_T_2 S12.min_T_2
## -6.331600e-01 5.643595e-01 -1.455571e+00
## S15.min_T_2 S17.min_T_2 S18.min_T_2
## -2.379445e+00 -3.176867e-01 1.782054e+00
## S1.min_T_2 S20.min_T_2 S2.min_T_2
## -8.833671e-02 3.840867e+00 -1.632051e+00
## S5.min_T_2 S6.min_T_2 S8.min_T_2
## -2.018952e+00 1.964106e+00 7.173884e-01
## S9.min_T_2 S12.15hs_T_2 S13.15hs_T_2
## -2.351665e-01 -2.133241e+00 3.335810e+00
## S14.15hs_T_2 S15.15hs_T_2 S16.15hs_T_2
## -2.603826e+00 -1.478589e+00 1.667398e+00
## S17.15hs_T_2 S18.15hs_T_2 S2.15hs_T_2
## -5.089534e+00 4.092371e+00 -1.058146e+00
## S3.15hs_T_2 S4.15hs_T_2 S5.15hs_T_2
## -2.152545e+00 2.130385e+00 -9.095683e-01
## S6.15hs_T_2 S7.15hs_T_2 S9.15hs_T_2
## 2.186636e+00 1.836052e+00 3.113074e-02
## S10.12hs_T_2 S11.12hs_T_2 S12.12hs_T_2
## -3.257625e-01 -1.296693e-01 -2.968218e+00
## S14.12hs_T_2 S15.12hs_T_2 S16.12hs_T_2
## -4.018358e-03 2.308718e+00 -1.233533e-01
## S17.12hs_T_2 S18.12hs_T_2 S1.12hs_T_2
## -3.859170e-01 1.049472e-01 -5.892723e-01
## S20.12hs_T_2 S2.12hs_T_2 S3.12hs_T_2
## -1.233696e-02 -1.873628e+00 -2.413525e-03
## S5.12hs_T_2 S7.12hs_T_2 S8.12hs_T_2
## 3.494793e+00 -1.158161e+00 1.605872e+00
## S10.18hs_T_2 S11.18hs_T_2 S14.18hs_T_2
## -1.524514e+00 -4.277947e-01 3.652561e+00
## S15.18hs_T_2 S16.18hs_T_2 S18.18hs_T_2
## 3.093922e+00 2.963839e-02 -8.574393e-01
## S1.18hs_T_2 S20.18hs_T_2 S2.18hs_T_2
## 1.849071e-01 2.272681e+00 1.155714e+00
## S3.18hs_T_2 S4.18hs_T_2 S5.18hs_T_2
## -2.869925e+00 -3.362129e+00 -7.835728e-03
## S6.18hs_T_2 S7.18hs_T_2 S8.18hs_T_2
## 1.394032e+00 1.239149e+00 -1.115265e+00
## S9.18hs_T_2 Est.humedad_med_T_2 Est.temp_max_T_2
## -3.052604e+00 7.732441e-02 5.042874e-01
## S10.max_T_1 S11.max_T_1 S14.max_T_1
## -1.462227e-01 1.818843e+00 1.257752e+00
## S15.max_T_1 S16.max_T_1 S17.max_T_1
## -1.368229e+00 -8.775722e-02 -4.134613e-01
## S19.max_T_1 S1.max_T_1 S20.max_T_1
## 1.379825e-01 -2.585175e+00 -7.187254e-01
## S2.max_T_1 S3.max_T_1 S4.max_T_1
## 1.710267e+00 -1.641045e+00 2.401178e-01
## S7.max_T_1 S8.max_T_1 S9.max_T_1
## -1.346155e+00 2.020744e+00 1.034276e+00
## S10.media_T_1 S11.media_T_1 S12.media_T_1
## -9.093713e+00 1.314209e+00 2.590301e+00
## S13.media_T_1 S14.media_T_1 S15.media_T_1
## -6.586182e-01 2.332879e+00 3.916631e-01
## S16.media_T_1 S18.media_T_1 S1.media_T_1
## 3.793583e+00 6.337082e+00 -7.692532e-01
## S2.media_T_1 S5.media_T_1 S6.media_T_1
## -7.460338e+00 -6.471900e+00 1.705191e+00
## S7.media_T_1 S8.media_T_1 S9.media_T_1
## 1.059573e+00 5.849559e+00 -1.382608e-01
## S12.min_T_1 S13.min_T_1 S14.min_T_1
## 3.922151e+00 7.995154e-01 -2.610525e+00
## S15.min_T_1 S17.min_T_1 S18.min_T_1
## 1.486930e+00 4.718768e-01 4.059753e-01
## S19.min_T_1 S1.min_T_1 S2.min_T_1
## -1.407719e+00 7.815618e-01 -1.997637e+00
## S3.min_T_1 S4.min_T_1 S5.min_T_1
## 1.850804e+00 -5.837303e-01 -5.571668e+00
## S6.min_T_1 S8.min_T_1 S10.15hs_T_1
## 2.128553e+00 3.525590e-01 -3.097068e+00
## S11.15hs_T_1 S12.15hs_T_1 S15.15hs_T_1
## -1.530831e+00 -1.821604e+00 -4.475528e-01
## S16.15hs_T_1 S18.15hs_T_1 S19.15hs_T_1
## -1.238261e+00 -6.110379e-02 1.266088e-01
## S1.15hs_T_1 S20.15hs_T_1 S2.15hs_T_1
## 8.128936e-01 3.078969e+00 -2.095653e+00
## S3.15hs_T_1 S4.15hs_T_1 S5.15hs_T_1
## 3.382080e+00 -1.727713e+00 1.772798e+00
## S6.15hs_T_1 S7.15hs_T_1 S9.15hs_T_1
## 1.361916e+00 1.118515e+00 3.478045e-01
## S10.12hs_T_1 S11.12hs_T_1 S12.12hs_T_1
## 1.381523e+00 -1.267317e+00 2.606571e-01
## S15.12hs_T_1 S16.12hs_T_1 S18.12hs_T_1
## 6.368564e-01 -6.436101e-01 4.563508e-01
## S19.12hs_T_1 S1.12hs_T_1 S20.12hs_T_1
## 2.970584e-01 -7.010697e-01 9.594750e-01
## S2.12hs_T_1 S3.12hs_T_1 S4.12hs_T_1
## -3.476020e-01 8.080276e-01 1.275057e+00
## S5.12hs_T_1 S6.12hs_T_1 S7.12hs_T_1
## -7.019574e-01 -2.530765e+00 1.800110e+00
## S8.12hs_T_1 S12.18hs_T_1 S13.18hs_T_1
## -1.379180e+00 1.432208e+00 5.015968e-02
## S14.18hs_T_1 S15.18hs_T_1 S1.18hs_T_1
## -8.173934e-01 9.078804e-01 -1.364792e+00
## S3.18hs_T_1 S5.18hs_T_1 S6.18hs_T_1
## 2.987799e+00 -4.670003e+00 4.896999e+00
## S7.18hs_T_1 S8.18hs_T_1 S9.18hs_T_1
## -1.505994e+00 -2.011788e+00 -2.789453e-02
## Est.humedad_min_T_1 Est.humedad_med_T_1 Est.temp_min_T_1
## 1.118845e+00 -1.139578e+00 6.079897e-03
## Standard deviation of the residuals: 2.231631e-08
##
## $S16.min_t
##
## Parameters of node S16.min_t (Gaussian distribution)
##
## Conditional density: S16.min_t | S11.max_T_2 + S12.max_T_2 + S13.max_T_2 + S14.max_T_2 + S15.max_T_2 + S16.max_T_2 + S17.max_T_2 + S20.max_T_2 + S2.max_T_2 + S5.max_T_2 + S6.max_T_2 + S7.max_T_2 + S9.max_T_2 + S10.media_T_2 + S15.media_T_2 + S16.media_T_2 + S17.media_T_2 + S18.media_T_2 + S1.media_T_2 + S2.media_T_2 + S3.media_T_2 + S4.media_T_2 + S6.media_T_2 + S7.media_T_2 + S11.min_T_2 + S12.min_T_2 + S16.min_T_2 + S17.min_T_2 + S18.min_T_2 + S19.min_T_2 + S1.min_T_2 + S2.min_T_2 + S3.min_T_2 + S4.min_T_2 + S5.min_T_2 + S9.min_T_2 + S11.15hs_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S14.15hs_T_2 + S15.15hs_T_2 + S16.15hs_T_2 + S17.15hs_T_2 + S19.15hs_T_2 + S1.15hs_T_2 + S3.15hs_T_2 + S4.15hs_T_2 + S5.15hs_T_2 + S6.15hs_T_2 + S7.15hs_T_2 + S9.15hs_T_2 + S12.12hs_T_2 + S13.12hs_T_2 + S14.12hs_T_2 + S16.12hs_T_2 + S17.12hs_T_2 + S18.12hs_T_2 + S2.12hs_T_2 + S4.12hs_T_2 + S6.12hs_T_2 + S7.12hs_T_2 + S8.12hs_T_2 + S10.18hs_T_2 + S12.18hs_T_2 + S13.18hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S16.18hs_T_2 + S17.18hs_T_2 + S18.18hs_T_2 + S1.18hs_T_2 + S20.18hs_T_2 + S2.18hs_T_2 + S3.18hs_T_2 + S4.18hs_T_2 + S5.18hs_T_2 + S6.18hs_T_2 + S7.18hs_T_2 + S9.18hs_T_2 + Est.humedad_min_T_2 + Est.temp_med_T_2 + S10.max_T_1 + S11.max_T_1 + S12.max_T_1 + S13.max_T_1 + S14.max_T_1 + S15.max_T_1 + S16.max_T_1 + S17.max_T_1 + S18.max_T_1 + S1.max_T_1 + S2.max_T_1 + S3.max_T_1 + S4.max_T_1 + S5.max_T_1 + S6.max_T_1 + S7.max_T_1 + S8.max_T_1 + S10.media_T_1 + S14.media_T_1 + S16.media_T_1 + S17.media_T_1 + S18.media_T_1 + S19.media_T_1 + S1.media_T_1 + S20.media_T_1 + S2.media_T_1 + S3.media_T_1 + S6.media_T_1 + S7.media_T_1 + S9.media_T_1 + S10.min_T_1 + S12.min_T_1 + S13.min_T_1 + S14.min_T_1 + S15.min_T_1 + S16.min_T_1 + S17.min_T_1 + S18.min_T_1 + S19.min_T_1 + S1.min_T_1 + S20.min_T_1 + S2.min_T_1 + S3.min_T_1 + S6.min_T_1 + S8.min_T_1 + S9.min_T_1 + S10.15hs_T_1 + S11.15hs_T_1 + S13.15hs_T_1 + S14.15hs_T_1 + S15.15hs_T_1 + S16.15hs_T_1 + S17.15hs_T_1 + S18.15hs_T_1 + S1.15hs_T_1 + S20.15hs_T_1 + S3.15hs_T_1 + S4.15hs_T_1 + S5.15hs_T_1 + S6.15hs_T_1 + S8.15hs_T_1 + S9.15hs_T_1 + S11.12hs_T_1 + S12.12hs_T_1 + S14.12hs_T_1 + S15.12hs_T_1 + S16.12hs_T_1 + S17.12hs_T_1 + S18.12hs_T_1 + S19.12hs_T_1 + S1.12hs_T_1 + S20.12hs_T_1 + S3.12hs_T_1 + S4.12hs_T_1 + S5.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S9.12hs_T_1 + S11.18hs_T_1 + S12.18hs_T_1 + S13.18hs_T_1 + S16.18hs_T_1 + S1.18hs_T_1 + S20.18hs_T_1 + S5.18hs_T_1 + S6.18hs_T_1 + S8.18hs_T_1 + S9.18hs_T_1 + Est.humedad_min_T_1 + Est.humedad_med_T_1 + Est.humedad_max_T_1 + Est.temp_min_T_1 + Est.temp_max_T_1 + Est.temp_med_T_1
## Coefficients:
## (Intercept) S11.max_T_2 S12.max_T_2
## -7.114000e-01 6.689059e-01 3.480928e-01
## S13.max_T_2 S14.max_T_2 S15.max_T_2
## 1.452903e+00 1.171980e+00 -6.583672e-01
## S16.max_T_2 S17.max_T_2 S20.max_T_2
## 3.563197e-01 -9.732577e-02 4.377354e-01
## S2.max_T_2 S5.max_T_2 S6.max_T_2
## -3.464871e+00 -1.539909e+00 1.307372e-01
## S7.max_T_2 S9.max_T_2 S10.media_T_2
## 9.984216e-01 1.412954e+00 -3.422541e+00
## S15.media_T_2 S16.media_T_2 S17.media_T_2
## 2.502367e+00 -1.090617e+00 -7.493128e+00
## S18.media_T_2 S1.media_T_2 S2.media_T_2
## -3.572998e-01 7.874639e+00 1.175833e+01
## S3.media_T_2 S4.media_T_2 S6.media_T_2
## -9.246908e+00 7.395710e+00 -5.374377e+00
## S7.media_T_2 S11.min_T_2 S12.min_T_2
## -2.561491e+00 7.149199e-01 9.166880e-01
## S16.min_T_2 S17.min_T_2 S18.min_T_2
## 1.401880e+00 -5.800829e-01 3.350910e-01
## S19.min_T_2 S1.min_T_2 S2.min_T_2
## 1.908026e-01 -2.325852e+00 -2.315878e+00
## S3.min_T_2 S4.min_T_2 S5.min_T_2
## 2.027115e+00 -4.098821e-01 -7.140513e-01
## S9.min_T_2 S11.15hs_T_2 S12.15hs_T_2
## 8.234768e-01 1.886979e+00 -2.587396e+00
## S13.15hs_T_2 S14.15hs_T_2 S15.15hs_T_2
## 4.512588e+00 -3.964182e+00 -7.345002e-01
## S16.15hs_T_2 S17.15hs_T_2 S19.15hs_T_2
## 1.904265e+00 -2.880054e-01 -1.581624e-01
## S1.15hs_T_2 S3.15hs_T_2 S4.15hs_T_2
## -7.980008e-01 -4.730299e-01 7.864725e-01
## S5.15hs_T_2 S6.15hs_T_2 S7.15hs_T_2
## -1.917435e+00 5.324972e+00 -3.500165e+00
## S9.15hs_T_2 S12.12hs_T_2 S13.12hs_T_2
## -4.906076e-03 1.604687e-02 6.998814e-01
## S14.12hs_T_2 S16.12hs_T_2 S17.12hs_T_2
## -1.195309e+00 -7.903395e-01 1.472267e+00
## S18.12hs_T_2 S2.12hs_T_2 S4.12hs_T_2
## 7.225772e-01 -8.326334e-01 5.299709e-01
## S6.12hs_T_2 S7.12hs_T_2 S8.12hs_T_2
## 3.017723e-01 -2.377795e+00 1.269370e+00
## S10.18hs_T_2 S12.18hs_T_2 S13.18hs_T_2
## -2.806334e+00 2.322429e+00 -5.293861e+00
## S14.18hs_T_2 S15.18hs_T_2 S16.18hs_T_2
## 3.934021e+00 3.636095e+00 -1.506185e-01
## S17.18hs_T_2 S18.18hs_T_2 S1.18hs_T_2
## -5.839857e-01 5.506758e-02 -8.727466e-01
## S20.18hs_T_2 S2.18hs_T_2 S3.18hs_T_2
## 1.333654e+00 3.703538e-01 1.413416e+00
## S4.18hs_T_2 S5.18hs_T_2 S6.18hs_T_2
## -4.444564e+00 -3.033620e+00 -4.965037e-03
## S7.18hs_T_2 S9.18hs_T_2 Est.humedad_min_T_2
## 2.847031e+00 4.018987e-01 -5.441575e-03
## Est.temp_med_T_2 S10.max_T_1 S11.max_T_1
## -1.651295e-05 2.567065e-01 1.400691e+00
## S12.max_T_1 S13.max_T_1 S14.max_T_1
## 8.507312e-01 -2.015094e+00 -1.947830e-01
## S15.max_T_1 S16.max_T_1 S17.max_T_1
## -1.401279e+00 -1.279876e+00 2.140167e+00
## S18.max_T_1 S1.max_T_1 S2.max_T_1
## 1.980392e-01 -1.395100e+00 9.351399e-01
## S3.max_T_1 S4.max_T_1 S5.max_T_1
## -2.505002e+00 8.068664e-01 1.414684e-01
## S6.max_T_1 S7.max_T_1 S8.max_T_1
## -7.204256e-01 -1.307766e+00 2.959445e+00
## S10.media_T_1 S14.media_T_1 S16.media_T_1
## 1.632818e+01 -1.247983e+00 5.313915e+00
## S17.media_T_1 S18.media_T_1 S19.media_T_1
## -7.828637e+00 2.151459e+00 4.492842e+00
## S1.media_T_1 S20.media_T_1 S2.media_T_1
## -1.225967e+00 -6.888684e+00 -3.328220e+00
## S3.media_T_1 S6.media_T_1 S7.media_T_1
## 4.351110e-01 4.506255e+00 5.900909e-01
## S9.media_T_1 S10.min_T_1 S12.min_T_1
## -1.251053e+01 2.856778e+00 4.978469e+00
## S13.min_T_1 S14.min_T_1 S15.min_T_1
## 1.639720e+00 -5.716776e+00 2.003098e+00
## S16.min_T_1 S17.min_T_1 S18.min_T_1
## -3.190325e+00 4.194889e-01 -2.668981e-01
## S19.min_T_1 S1.min_T_1 S20.min_T_1
## 8.762670e-01 1.330008e+00 -4.545429e-01
## S2.min_T_1 S3.min_T_1 S6.min_T_1
## -5.311391e-01 -3.378644e-01 7.049414e-01
## S8.min_T_1 S9.min_T_1 S10.15hs_T_1
## -2.682742e+00 -1.702183e+00 -3.947849e+00
## S11.15hs_T_1 S13.15hs_T_1 S14.15hs_T_1
## -1.733536e+00 7.547385e-01 2.243420e+00
## S15.15hs_T_1 S16.15hs_T_1 S17.15hs_T_1
## -1.956852e+00 -2.757114e+00 3.197073e-01
## S18.15hs_T_1 S1.15hs_T_1 S20.15hs_T_1
## 7.494326e-01 1.069282e+00 1.743341e+00
## S3.15hs_T_1 S4.15hs_T_1 S5.15hs_T_1
## 3.116438e+00 -8.513040e-01 1.583898e-01
## S6.15hs_T_1 S8.15hs_T_1 S9.15hs_T_1
## 7.125709e-01 -3.177810e-01 1.720949e+00
## S11.12hs_T_1 S12.12hs_T_1 S14.12hs_T_1
## 7.284880e-01 -1.761246e+00 -3.965489e-02
## S15.12hs_T_1 S16.12hs_T_1 S17.12hs_T_1
## -3.354035e-01 1.557536e+00 -1.202999e+00
## S18.12hs_T_1 S19.12hs_T_1 S1.12hs_T_1
## -1.050876e-01 8.760819e-01 -6.330777e-02
## S20.12hs_T_1 S3.12hs_T_1 S4.12hs_T_1
## -9.050473e-02 2.364189e-02 2.108053e+00
## S5.12hs_T_1 S6.12hs_T_1 S7.12hs_T_1
## -1.958897e+00 -3.996167e+00 4.973077e+00
## S8.12hs_T_1 S9.12hs_T_1 S11.18hs_T_1
## -2.567134e+00 2.142637e+00 1.755819e+00
## S12.18hs_T_1 S13.18hs_T_1 S16.18hs_T_1
## 3.345868e-01 -7.579496e-01 -1.641525e+00
## S1.18hs_T_1 S20.18hs_T_1 S5.18hs_T_1
## -2.643975e-01 1.112449e+00 -1.605804e+00
## S6.18hs_T_1 S8.18hs_T_1 S9.18hs_T_1
## 3.113637e+00 -3.973519e-01 -1.683835e+00
## Est.humedad_min_T_1 Est.humedad_med_T_1 Est.humedad_max_T_1
## -5.362567e-03 6.618146e-02 -7.220636e-02
## Est.temp_min_T_1 Est.temp_max_T_1 Est.temp_med_T_1
## 7.505367e+00 4.604943e+00 -1.226731e+01
## Standard deviation of the residuals: 5.641661e-08
##
## $S18.min_t
##
## Parameters of node S18.min_t (Gaussian distribution)
##
## Conditional density: S18.min_t | S18.max_T_2 + S5.max_T_2 + S18.media_T_2 + S4.media_T_2 + S12.min_T_2 + S16.min_T_2 + S18.min_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S18.15hs_T_2 + S18.12hs_T_2 + S18.18hs_T_2 + S1.18hs_T_2 + Est.temp_min_T_2 + Est.temp_max_T_2 + S13.max_T_1 + S18.max_T_1 + S2.max_T_1 + S18.media_T_1 + S20.media_T_1 + S8.media_T_1 + S9.media_T_1 + S15.min_T_1 + S18.min_T_1 + S18.15hs_T_1 + S18.12hs_T_1 + S4.12hs_T_1 + S8.12hs_T_1 + S12.18hs_T_1 + S18.18hs_T_1 + Est.humedad_min_T_1
## Coefficients:
## (Intercept) S18.max_T_2 S5.max_T_2
## -5.381962093 1.074500278 -0.909682146
## S18.media_T_2 S4.media_T_2 S12.min_T_2
## -3.958021028 3.738595666 0.963977267
## S16.min_T_2 S18.min_T_2 S12.15hs_T_2
## -1.509784086 0.787350766 -0.951271250
## S13.15hs_T_2 S18.15hs_T_2 S18.12hs_T_2
## 2.002179789 -1.029748180 -0.085457797
## S18.18hs_T_2 S1.18hs_T_2 Est.temp_min_T_2
## 0.742234664 -0.745686791 0.610075675
## Est.temp_max_T_2 S13.max_T_1 S18.max_T_1
## -0.472701323 -1.431836979 -0.002788392
## S2.max_T_1 S18.media_T_1 S20.media_T_1
## 1.419684895 0.811094370 -1.923214618
## S8.media_T_1 S9.media_T_1 S15.min_T_1
## 7.704356712 -6.254563387 0.963276655
## S18.min_T_1 S18.15hs_T_1 S18.12hs_T_1
## -0.686954555 0.307218137 0.196849384
## S4.12hs_T_1 S8.12hs_T_1 S12.18hs_T_1
## 0.883005719 -1.128755332 0.455091142
## S18.18hs_T_1 Est.humedad_min_T_1
## -0.529766757 0.041665114
## Standard deviation of the residuals: 1.360919
##
## $S19.min_t
##
## Parameters of node S19.min_t (Gaussian distribution)
##
## Conditional density: S19.min_t | S19.max_T_2 + S19.media_T_2 + S4.media_T_2 + S19.min_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S14.15hs_T_2 + S17.15hs_T_2 + S19.15hs_T_2 + S19.12hs_T_2 + S10.18hs_T_2 + S14.18hs_T_2 + S19.18hs_T_2 + S4.18hs_T_2 + Est.temp_min_T_2 + S19.max_T_1 + S13.media_T_1 + S19.media_T_1 + S2.media_T_1 + S9.media_T_1 + S19.min_T_1 + S1.min_T_1 + S19.15hs_T_1 + S19.12hs_T_1 + S4.12hs_T_1 + S12.18hs_T_1 + S19.18hs_T_1 + Est.humedad_min_T_1
## Coefficients:
## (Intercept) S19.max_T_2 S19.media_T_2
## -6.64357721 0.18941101 -4.56637022
## S4.media_T_2 S19.min_T_2 S12.15hs_T_2
## 4.46001218 0.11968879 -0.97748653
## S13.15hs_T_2 S14.15hs_T_2 S17.15hs_T_2
## 2.47565170 -0.76134217 -0.50915172
## S19.15hs_T_2 S19.12hs_T_2 S10.18hs_T_2
## -0.10029141 -0.36799041 -1.17869421
## S14.18hs_T_2 S19.18hs_T_2 S4.18hs_T_2
## 1.47998905 0.57446874 -0.84450776
## Est.temp_min_T_2 S19.max_T_1 S13.media_T_1
## 0.22945698 -0.04634780 -4.57262113
## S19.media_T_1 S2.media_T_1 S9.media_T_1
## 6.14328374 5.13028793 -6.78846722
## S19.min_T_1 S1.min_T_1 S19.15hs_T_1
## -0.17797287 0.72681748 0.31628730
## S19.12hs_T_1 S4.12hs_T_1 S12.18hs_T_1
## -0.36381886 0.43488257 0.55059638
## S19.18hs_T_1 Est.humedad_min_T_1
## -0.54686742 0.04392422
## Standard deviation of the residuals: 1.461595
##
## $S1.min_t
##
## Parameters of node S1.min_t (Gaussian distribution)
##
## Conditional density: S1.min_t | S16.max_T_2 + S1.max_T_2 + S4.max_T_2 + S12.media_T_2 + S15.media_T_2 + S17.media_T_2 + S1.media_T_2 + S4.media_T_2 + S6.media_T_2 + S12.min_T_2 + S16.min_T_2 + S1.min_T_2 + S13.15hs_T_2 + S17.15hs_T_2 + S1.15hs_T_2 + S5.15hs_T_2 + S19.12hs_T_2 + S1.12hs_T_2 + S14.18hs_T_2 + S1.18hs_T_2 + S6.18hs_T_2 + S9.18hs_T_2 + Est.temp_min_T_2 + Est.temp_med_T_2 + S1.max_T_1 + S2.max_T_1 + S9.max_T_1 + S13.media_T_1 + S1.media_T_1 + S8.media_T_1 + S9.media_T_1 + S12.min_T_1 + S1.min_T_1 + S8.min_T_1 + S12.15hs_T_1 + S1.15hs_T_1 + S16.12hs_T_1 + S1.12hs_T_1 + S4.12hs_T_1 + S1.18hs_T_1 + S3.18hs_T_1 + S8.18hs_T_1 + Est.humedad_med_T_1
## Coefficients:
## (Intercept) S16.max_T_2 S1.max_T_2
## -5.72645747 1.04427900 -0.51413444
## S4.max_T_2 S12.media_T_2 S15.media_T_2
## -0.42720837 -2.42295479 -1.76718362
## S17.media_T_2 S1.media_T_2 S4.media_T_2
## -2.17198218 -2.79720787 5.14020973
## S6.media_T_2 S12.min_T_2 S16.min_T_2
## 4.27413626 1.81845933 -1.71273324
## S1.min_T_2 S13.15hs_T_2 S17.15hs_T_2
## -0.10962645 1.95527300 -0.67320067
## S1.15hs_T_2 S5.15hs_T_2 S19.12hs_T_2
## 0.25132415 -1.53007437 -0.60507023
## S1.12hs_T_2 S14.18hs_T_2 S1.18hs_T_2
## 0.34917532 3.01888545 -0.79089788
## S6.18hs_T_2 S9.18hs_T_2 Est.temp_min_T_2
## -1.36177707 -0.74152529 1.07468040
## Est.temp_med_T_2 S1.max_T_1 S2.max_T_1
## -0.90685650 -0.77280238 1.47176696
## S9.max_T_1 S13.media_T_1 S1.media_T_1
## -0.78716627 -3.51623628 3.90219693
## S8.media_T_1 S9.media_T_1 S12.min_T_1
## 3.89795485 -4.48681617 1.48109505
## S1.min_T_1 S8.min_T_1 S12.15hs_T_1
## 0.41999126 -1.44532496 -0.85139194
## S1.15hs_T_1 S16.12hs_T_1 S1.12hs_T_1
## 1.33183347 -0.41952162 -0.52586073
## S4.12hs_T_1 S1.18hs_T_1 S3.18hs_T_1
## 0.92194707 0.16938800 -0.72549108
## S8.18hs_T_1 Est.humedad_med_T_1
## 0.56595446 0.02894895
## Standard deviation of the residuals: 1.217089
##
## $S20.min_t
##
## Parameters of node S20.min_t (Gaussian distribution)
##
## Conditional density: S20.min_t | S10.max_T_2 + S11.max_T_2 + S12.max_T_2 + S13.max_T_2 + S14.max_T_2 + S17.max_T_2 + S1.max_T_2 + S20.max_T_2 + S2.max_T_2 + S4.max_T_2 + S5.max_T_2 + S6.max_T_2 + S8.max_T_2 + S9.max_T_2 + S10.media_T_2 + S11.media_T_2 + S12.media_T_2 + S13.media_T_2 + S15.media_T_2 + S17.media_T_2 + S18.media_T_2 + S19.media_T_2 + S20.media_T_2 + S2.media_T_2 + S3.media_T_2 + S4.media_T_2 + S7.media_T_2 + S8.media_T_2 + S10.min_T_2 + S11.min_T_2 + S12.min_T_2 + S14.min_T_2 + S16.min_T_2 + S17.min_T_2 + S18.min_T_2 + S20.min_T_2 + S2.min_T_2 + S5.min_T_2 + S6.min_T_2 + S7.min_T_2 + S8.min_T_2 + S9.min_T_2 + S10.15hs_T_2 + S11.15hs_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S15.15hs_T_2 + S16.15hs_T_2 + S17.15hs_T_2 + S18.15hs_T_2 + S1.15hs_T_2 + S20.15hs_T_2 + S2.15hs_T_2 + S4.15hs_T_2 + S5.15hs_T_2 + S6.15hs_T_2 + S7.15hs_T_2 + S9.15hs_T_2 + S10.12hs_T_2 + S11.12hs_T_2 + S12.12hs_T_2 + S13.12hs_T_2 + S14.12hs_T_2 + S15.12hs_T_2 + S17.12hs_T_2 + S18.12hs_T_2 + S20.12hs_T_2 + S2.12hs_T_2 + S5.12hs_T_2 + S7.12hs_T_2 + S10.18hs_T_2 + S11.18hs_T_2 + S13.18hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S18.18hs_T_2 + S1.18hs_T_2 + S20.18hs_T_2 + S2.18hs_T_2 + S5.18hs_T_2 + S6.18hs_T_2 + S7.18hs_T_2 + S9.18hs_T_2 + Est.humedad_min_T_2 + Est.humedad_med_T_2 + Est.humedad_max_T_2 + Est.temp_max_T_2 + S10.max_T_1 + S11.max_T_1 + S12.max_T_1 + S13.max_T_1 + S14.max_T_1 + S15.max_T_1 + S17.max_T_1 + S19.max_T_1 + S20.max_T_1 + S2.max_T_1 + S3.max_T_1 + S4.max_T_1 + S5.max_T_1 + S6.max_T_1 + S7.max_T_1 + S8.max_T_1 + S10.media_T_1 + S11.media_T_1 + S12.media_T_1 + S13.media_T_1 + S14.media_T_1 + S16.media_T_1 + S17.media_T_1 + S18.media_T_1 + S20.media_T_1 + S2.media_T_1 + S3.media_T_1 + S4.media_T_1 + S5.media_T_1 + S6.media_T_1 + S7.media_T_1 + S8.media_T_1 + S9.media_T_1 + S12.min_T_1 + S13.min_T_1 + S14.min_T_1 + S15.min_T_1 + S16.min_T_1 + S17.min_T_1 + S18.min_T_1 + S19.min_T_1 + S20.min_T_1 + S2.min_T_1 + S3.min_T_1 + S4.min_T_1 + S5.min_T_1 + S7.min_T_1 + S8.min_T_1 + S9.min_T_1 + S10.15hs_T_1 + S11.15hs_T_1 + S13.15hs_T_1 + S14.15hs_T_1 + S15.15hs_T_1 + S16.15hs_T_1 + S19.15hs_T_1 + S20.15hs_T_1 + S2.15hs_T_1 + S3.15hs_T_1 + S4.15hs_T_1 + S7.15hs_T_1 + S8.15hs_T_1 + S10.12hs_T_1 + S14.12hs_T_1 + S15.12hs_T_1 + S17.12hs_T_1 + S19.12hs_T_1 + S1.12hs_T_1 + S20.12hs_T_1 + S2.12hs_T_1 + S3.12hs_T_1 + S4.12hs_T_1 + S5.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S9.12hs_T_1 + S11.18hs_T_1 + S13.18hs_T_1 + S17.18hs_T_1 + S18.18hs_T_1 + S20.18hs_T_1 + S3.18hs_T_1 + S4.18hs_T_1 + S5.18hs_T_1 + S7.18hs_T_1 + S8.18hs_T_1 + Est.humedad_med_T_1 + Est.temp_max_T_1
## Coefficients:
## (Intercept) S10.max_T_2 S11.max_T_2
## -1.200927e+01 -2.717120e+00 -6.778034e-01
## S12.max_T_2 S13.max_T_2 S14.max_T_2
## 1.020086e+00 2.298489e-01 7.650800e-02
## S17.max_T_2 S1.max_T_2 S20.max_T_2
## 1.709640e+00 -4.091903e-01 1.769491e+00
## S2.max_T_2 S4.max_T_2 S5.max_T_2
## -4.344834e-01 4.900806e-01 -2.801213e+00
## S6.max_T_2 S8.max_T_2 S9.max_T_2
## -1.039863e-01 -1.434822e-03 1.535629e+00
## S10.media_T_2 S11.media_T_2 S12.media_T_2
## -9.098410e+00 -2.008864e-01 6.720389e+00
## S13.media_T_2 S15.media_T_2 S17.media_T_2
## -7.677276e+00 -4.382043e+00 -1.131575e+00
## S18.media_T_2 S19.media_T_2 S20.media_T_2
## -2.054055e-02 -3.020089e-01 4.330497e-01
## S2.media_T_2 S3.media_T_2 S4.media_T_2
## 1.222110e+00 -3.851853e+00 1.341144e+00
## S7.media_T_2 S8.media_T_2 S10.min_T_2
## 1.238502e+01 4.220310e+00 2.483078e+00
## S11.min_T_2 S12.min_T_2 S14.min_T_2
## 1.989635e+00 -2.879582e+00 1.054572e-01
## S16.min_T_2 S17.min_T_2 S18.min_T_2
## 1.120687e+00 -1.922615e-02 9.262837e-01
## S20.min_T_2 S2.min_T_2 S5.min_T_2
## 1.165933e+00 -9.590010e-01 1.713676e-01
## S6.min_T_2 S7.min_T_2 S8.min_T_2
## 1.520637e-01 -2.243377e+00 4.055281e-01
## S9.min_T_2 S10.15hs_T_2 S11.15hs_T_2
## -2.228424e+00 4.356829e-01 1.406715e+00
## S12.15hs_T_2 S13.15hs_T_2 S15.15hs_T_2
## -2.652930e+00 5.147731e+00 -4.213728e-01
## S16.15hs_T_2 S17.15hs_T_2 S18.15hs_T_2
## -3.430381e-01 -2.850236e+00 7.955118e-01
## S1.15hs_T_2 S20.15hs_T_2 S2.15hs_T_2
## -7.038588e-01 -1.015083e+00 -9.680895e-01
## S4.15hs_T_2 S5.15hs_T_2 S6.15hs_T_2
## 3.054229e+00 7.870608e-01 7.939637e-01
## S7.15hs_T_2 S9.15hs_T_2 S10.12hs_T_2
## -1.823225e+00 -1.360596e+00 3.374262e-02
## S11.12hs_T_2 S12.12hs_T_2 S13.12hs_T_2
## -1.054850e+00 -1.613038e+00 -4.049708e-01
## S14.12hs_T_2 S15.12hs_T_2 S17.12hs_T_2
## 1.418729e-01 2.344656e+00 -2.432995e-01
## S18.12hs_T_2 S20.12hs_T_2 S2.12hs_T_2
## 4.923706e-01 2.107836e-01 9.441972e-01
## S5.12hs_T_2 S7.12hs_T_2 S10.18hs_T_2
## 4.948873e-01 -1.513973e+00 1.637418e-01
## S11.18hs_T_2 S13.18hs_T_2 S14.18hs_T_2
## 6.734180e-02 -5.114328e-02 2.454305e+00
## S15.18hs_T_2 S18.18hs_T_2 S1.18hs_T_2
## 1.845742e+00 -1.152171e+00 -2.035358e+00
## S20.18hs_T_2 S2.18hs_T_2 S5.18hs_T_2
## -5.260403e-02 -4.897579e-01 1.454976e+00
## S6.18hs_T_2 S7.18hs_T_2 S9.18hs_T_2
## -2.255625e+00 -1.002992e+00 1.192338e+00
## Est.humedad_min_T_2 Est.humedad_med_T_2 Est.humedad_max_T_2
## -5.538058e-01 3.837839e-01 1.286748e-01
## Est.temp_max_T_2 S10.max_T_1 S11.max_T_1
## -3.413850e-02 4.054723e-01 8.340587e-01
## S12.max_T_1 S13.max_T_1 S14.max_T_1
## -2.602601e-01 -1.281913e+00 8.072738e-01
## S15.max_T_1 S17.max_T_1 S19.max_T_1
## -2.729924e+00 5.729329e-01 -9.011979e-01
## S20.max_T_1 S2.max_T_1 S3.max_T_1
## -1.009226e+00 2.444510e+00 -2.050745e+00
## S4.max_T_1 S5.max_T_1 S6.max_T_1
## 8.376319e-04 6.779298e-02 -3.628933e-01
## S7.max_T_1 S8.max_T_1 S10.media_T_1
## -1.729511e-01 2.845207e+00 1.125829e+01
## S11.media_T_1 S12.media_T_1 S13.media_T_1
## 5.141444e-02 -2.927425e-01 -1.021418e+00
## S14.media_T_1 S16.media_T_1 S17.media_T_1
## -9.411015e+00 1.433786e+00 -4.523330e+00
## S18.media_T_1 S20.media_T_1 S2.media_T_1
## 7.557399e+00 -6.528011e+00 2.748891e+00
## S3.media_T_1 S4.media_T_1 S5.media_T_1
## 7.778656e+00 1.507638e+00 -1.041229e+01
## S6.media_T_1 S7.media_T_1 S8.media_T_1
## 1.263354e+01 -1.317295e+01 6.141227e+00
## S9.media_T_1 S12.min_T_1 S13.min_T_1
## -4.419100e+00 2.063390e+00 -2.724996e+00
## S14.min_T_1 S15.min_T_1 S16.min_T_1
## -1.646477e+00 3.813178e+00 1.165811e+00
## S17.min_T_1 S18.min_T_1 S19.min_T_1
## 1.870424e-01 1.490006e+00 -2.889798e+00
## S20.min_T_1 S2.min_T_1 S3.min_T_1
## -4.025636e-01 1.777116e-01 3.755048e+00
## S4.min_T_1 S5.min_T_1 S7.min_T_1
## -2.876356e+00 -1.074292e+00 -1.265425e+00
## S8.min_T_1 S9.min_T_1 S10.15hs_T_1
## -9.660973e-03 2.923635e-01 -2.838508e+00
## S11.15hs_T_1 S13.15hs_T_1 S14.15hs_T_1
## -2.298396e+00 -1.155916e-02 2.621418e-01
## S15.15hs_T_1 S16.15hs_T_1 S19.15hs_T_1
## 1.084997e+00 -1.819203e-04 1.505535e+00
## S20.15hs_T_1 S2.15hs_T_1 S3.15hs_T_1
## 1.645665e+00 -1.298681e-01 1.257128e+00
## S4.15hs_T_1 S7.15hs_T_1 S8.15hs_T_1
## -6.324889e-01 1.967522e+00 -1.019025e+00
## S10.12hs_T_1 S14.12hs_T_1 S15.12hs_T_1
## 1.289709e+00 -5.853382e-01 -6.385847e-01
## S17.12hs_T_1 S19.12hs_T_1 S1.12hs_T_1
## -2.330205e-01 9.712796e-01 -7.729089e-01
## S20.12hs_T_1 S2.12hs_T_1 S3.12hs_T_1
## -8.896752e-02 6.856113e-01 2.172914e+00
## S4.12hs_T_1 S5.12hs_T_1 S6.12hs_T_1
## 8.591714e-02 -1.175070e+00 -1.188939e+00
## S7.12hs_T_1 S8.12hs_T_1 S9.12hs_T_1
## 1.394584e+00 -1.605317e+00 -3.372668e-01
## S11.18hs_T_1 S13.18hs_T_1 S17.18hs_T_1
## 4.913223e-01 4.190801e+00 -1.315988e+00
## S18.18hs_T_1 S20.18hs_T_1 S3.18hs_T_1
## -1.040826e+00 1.551819e+00 2.072459e+00
## S4.18hs_T_1 S5.18hs_T_1 S7.18hs_T_1
## -1.409102e-02 -1.203326e+00 -3.128948e+00
## S8.18hs_T_1 Est.humedad_med_T_1 Est.temp_max_T_1
## -1.517628e+00 6.357376e-02 6.574632e-02
## Standard deviation of the residuals: 1.103777e-07
##
## $S2.min_t
##
## Parameters of node S2.min_t (Gaussian distribution)
##
## Conditional density: S2.min_t | S11.max_T_2 + S12.max_T_2 + S13.max_T_2 + S14.max_T_2 + S15.max_T_2 + S16.max_T_2 + S17.max_T_2 + S18.max_T_2 + S1.max_T_2 + S20.max_T_2 + S2.max_T_2 + S3.max_T_2 + S6.max_T_2 + S7.max_T_2 + S8.max_T_2 + S10.media_T_2 + S11.media_T_2 + S12.media_T_2 + S13.media_T_2 + S14.media_T_2 + S17.media_T_2 + S18.media_T_2 + S1.media_T_2 + S20.media_T_2 + S2.media_T_2 + S3.media_T_2 + S4.media_T_2 + S5.media_T_2 + S6.media_T_2 + S7.media_T_2 + S8.media_T_2 + S9.media_T_2 + S10.min_T_2 + S11.min_T_2 + S12.min_T_2 + S13.min_T_2 + S15.min_T_2 + S16.min_T_2 + S17.min_T_2 + S18.min_T_2 + S1.min_T_2 + S20.min_T_2 + S2.min_T_2 + S3.min_T_2 + S5.min_T_2 + S6.min_T_2 + S7.min_T_2 + S8.min_T_2 + S9.min_T_2 + S10.15hs_T_2 + S11.15hs_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S16.15hs_T_2 + S17.15hs_T_2 + S18.15hs_T_2 + S19.15hs_T_2 + S1.15hs_T_2 + S20.15hs_T_2 + S2.15hs_T_2 + S4.15hs_T_2 + S5.15hs_T_2 + S6.15hs_T_2 + S9.15hs_T_2 + S10.12hs_T_2 + S11.12hs_T_2 + S12.12hs_T_2 + S14.12hs_T_2 + S15.12hs_T_2 + S17.12hs_T_2 + S18.12hs_T_2 + S19.12hs_T_2 + S1.12hs_T_2 + S20.12hs_T_2 + S2.12hs_T_2 + S5.12hs_T_2 + S7.12hs_T_2 + S8.12hs_T_2 + S9.12hs_T_2 + S10.18hs_T_2 + S11.18hs_T_2 + S12.18hs_T_2 + S13.18hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S17.18hs_T_2 + S19.18hs_T_2 + S1.18hs_T_2 + S2.18hs_T_2 + S3.18hs_T_2 + S5.18hs_T_2 + S6.18hs_T_2 + S8.18hs_T_2 + Est.temp_min_T_2 + Est.temp_max_T_2 + Est.temp_med_T_2 + S11.max_T_1 + S12.max_T_1 + S13.max_T_1 + S15.max_T_1 + S18.max_T_1 + S1.max_T_1 + S20.max_T_1 + S2.max_T_1 + S4.max_T_1 + S5.max_T_1 + S7.max_T_1 + S9.max_T_1 + S13.media_T_1 + S15.media_T_1 + S16.media_T_1 + S1.media_T_1 + S2.media_T_1 + S3.media_T_1 + S4.media_T_1 + S5.media_T_1 + S8.media_T_1 + S10.min_T_1 + S11.min_T_1 + S12.min_T_1 + S13.min_T_1 + S14.min_T_1 + S16.min_T_1 + S17.min_T_1 + S18.min_T_1 + S2.min_T_1 + S4.min_T_1 + S6.min_T_1 + S8.min_T_1 + S9.min_T_1 + S13.15hs_T_1 + S15.15hs_T_1 + S16.15hs_T_1 + S18.15hs_T_1 + S19.15hs_T_1 + S1.15hs_T_1 + S2.15hs_T_1 + S3.15hs_T_1 + S4.15hs_T_1 + S5.15hs_T_1 + S8.15hs_T_1 + S10.12hs_T_1 + S12.12hs_T_1 + S13.12hs_T_1 + S14.12hs_T_1 + S15.12hs_T_1 + S1.12hs_T_1 + S20.12hs_T_1 + S2.12hs_T_1 + S4.12hs_T_1 + S5.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S9.12hs_T_1 + S10.18hs_T_1 + S11.18hs_T_1 + S12.18hs_T_1 + S13.18hs_T_1 + S17.18hs_T_1 + S18.18hs_T_1 + S19.18hs_T_1 + S1.18hs_T_1 + S2.18hs_T_1 + S3.18hs_T_1 + S4.18hs_T_1 + S5.18hs_T_1 + S6.18hs_T_1 + S7.18hs_T_1 + S8.18hs_T_1 + Est.humedad_min_T_1 + Est.humedad_med_T_1 + Est.humedad_max_T_1 + Est.temp_min_T_1 + Est.temp_max_T_1 + Est.temp_med_T_1
## Coefficients:
## (Intercept) S11.max_T_2 S12.max_T_2
## 6.482633e-01 5.038625e-01 1.455015e-01
## S13.max_T_2 S14.max_T_2 S15.max_T_2
## 1.377015e+00 9.281161e-01 -4.122140e-01
## S16.max_T_2 S17.max_T_2 S18.max_T_2
## 1.539215e+00 3.429756e-01 -5.812467e-01
## S1.max_T_2 S20.max_T_2 S2.max_T_2
## 9.629157e-01 9.697597e-01 -4.331309e+00
## S3.max_T_2 S6.max_T_2 S7.max_T_2
## 6.248313e-02 -6.805983e-01 1.055690e+00
## S8.max_T_2 S10.media_T_2 S11.media_T_2
## -7.153765e-01 -1.846331e+00 -1.001793e+01
## S12.media_T_2 S13.media_T_2 S14.media_T_2
## -6.748994e+00 -4.027973e+00 2.331017e-03
## S17.media_T_2 S18.media_T_2 S1.media_T_2
## -5.975952e+00 -3.004851e+00 -1.374539e+00
## S20.media_T_2 S2.media_T_2 S3.media_T_2
## 6.828467e+00 6.516792e+00 -3.679858e+00
## S4.media_T_2 S5.media_T_2 S6.media_T_2
## 9.293046e+00 9.137604e+00 -5.231522e+00
## S7.media_T_2 S8.media_T_2 S9.media_T_2
## 8.400731e+00 4.353480e-02 8.093162e-02
## S10.min_T_2 S11.min_T_2 S12.min_T_2
## 3.684667e+00 1.070975e-02 4.976205e-01
## S13.min_T_2 S15.min_T_2 S16.min_T_2
## 4.138970e+00 -8.997690e-01 1.856754e-01
## S17.min_T_2 S18.min_T_2 S1.min_T_2
## 1.725301e+00 6.490128e-02 -6.529988e-01
## S20.min_T_2 S2.min_T_2 S3.min_T_2
## 1.871348e+00 -2.228989e+00 -9.617868e-02
## S5.min_T_2 S6.min_T_2 S7.min_T_2
## -1.147397e+00 -3.451971e-01 -1.164498e+00
## S8.min_T_2 S9.min_T_2 S10.15hs_T_2
## 1.028445e-02 -4.927290e+00 -7.399682e-01
## S11.15hs_T_2 S12.15hs_T_2 S13.15hs_T_2
## 1.261860e+00 -4.297850e-01 1.726458e+00
## S16.15hs_T_2 S17.15hs_T_2 S18.15hs_T_2
## 1.557264e-03 -2.507365e+00 1.558844e+00
## S19.15hs_T_2 S1.15hs_T_2 S20.15hs_T_2
## -6.713181e-02 -1.573549e+00 -3.889265e-01
## S2.15hs_T_2 S4.15hs_T_2 S5.15hs_T_2
## 2.634521e+00 -1.481579e+00 -1.293305e+00
## S6.15hs_T_2 S9.15hs_T_2 S10.12hs_T_2
## 3.118092e+00 -1.792270e+00 1.011236e-02
## S11.12hs_T_2 S12.12hs_T_2 S14.12hs_T_2
## 2.431061e-01 7.252988e-01 -1.407202e+00
## S15.12hs_T_2 S17.12hs_T_2 S18.12hs_T_2
## -1.043377e+00 5.401653e-01 -4.789965e-02
## S19.12hs_T_2 S1.12hs_T_2 S20.12hs_T_2
## -3.115683e-03 -7.401100e-01 -5.013027e-01
## S2.12hs_T_2 S5.12hs_T_2 S7.12hs_T_2
## 6.797644e-01 2.475795e-01 -1.453054e+00
## S8.12hs_T_2 S9.12hs_T_2 S10.18hs_T_2
## -7.631302e-04 2.723560e+00 -5.330685e+00
## S11.18hs_T_2 S12.18hs_T_2 S13.18hs_T_2
## -1.431220e+00 2.080210e+00 -2.926819e-01
## S14.18hs_T_2 S15.18hs_T_2 S17.18hs_T_2
## 2.950425e+00 2.733601e+00 2.260694e+00
## S19.18hs_T_2 S1.18hs_T_2 S2.18hs_T_2
## 1.468029e+00 2.086988e-01 -1.709779e+00
## S3.18hs_T_2 S5.18hs_T_2 S6.18hs_T_2
## -7.066520e-01 -4.570581e+00 2.288689e+00
## S8.18hs_T_2 Est.temp_min_T_2 Est.temp_max_T_2
## -4.531518e-01 -2.985103e-01 1.431933e-02
## Est.temp_med_T_2 S11.max_T_1 S12.max_T_1
## 7.262450e-01 1.788152e+00 -2.439217e-01
## S13.max_T_1 S15.max_T_1 S18.max_T_1
## 5.773185e-01 -2.784865e-02 4.016552e-01
## S1.max_T_1 S20.max_T_1 S2.max_T_1
## -1.883072e+00 -1.377549e+00 8.209282e-01
## S4.max_T_1 S5.max_T_1 S7.max_T_1
## 1.713966e+00 -6.248368e-01 -1.838115e-02
## S9.max_T_1 S13.media_T_1 S15.media_T_1
## -1.402888e+00 -3.114719e+00 -1.932168e+00
## S16.media_T_1 S1.media_T_1 S2.media_T_1
## 4.864299e+00 1.640201e+00 5.781622e+00
## S3.media_T_1 S4.media_T_1 S5.media_T_1
## -6.130794e-01 6.487324e+00 -2.018227e+01
## S8.media_T_1 S10.min_T_1 S11.min_T_1
## 8.346735e+00 4.827000e+00 4.715373e+00
## S12.min_T_1 S13.min_T_1 S14.min_T_1
## 5.904899e+00 4.657049e-01 -3.693500e+00
## S16.min_T_1 S17.min_T_1 S18.min_T_1
## -4.492645e+00 1.406724e+00 5.778612e-02
## S2.min_T_1 S4.min_T_1 S6.min_T_1
## -2.812697e-01 -3.121019e+00 -1.442925e+00
## S8.min_T_1 S9.min_T_1 S13.15hs_T_1
## -4.306849e+00 -9.284577e-02 4.406781e-01
## S15.15hs_T_1 S16.15hs_T_1 S18.15hs_T_1
## 9.868939e-01 -1.552205e+00 6.765229e-01
## S19.15hs_T_1 S1.15hs_T_1 S2.15hs_T_1
## 6.410809e-02 -1.496420e-01 -2.205384e+00
## S3.15hs_T_1 S4.15hs_T_1 S5.15hs_T_1
## 3.116710e+00 -2.774305e+00 2.368067e+00
## S8.15hs_T_1 S10.12hs_T_1 S12.12hs_T_1
## -5.563152e-01 1.058399e+00 -2.668661e-01
## S13.12hs_T_1 S14.12hs_T_1 S15.12hs_T_1
## -1.160920e+00 2.606698e+00 -1.409969e+00
## S1.12hs_T_1 S20.12hs_T_1 S2.12hs_T_1
## -5.644536e-01 -9.419116e-02 -5.413080e-02
## S4.12hs_T_1 S5.12hs_T_1 S6.12hs_T_1
## 2.199345e-03 1.834266e+00 -2.401984e+00
## S7.12hs_T_1 S8.12hs_T_1 S9.12hs_T_1
## 1.743606e+00 -9.440388e-01 -3.747261e-01
## S10.18hs_T_1 S11.18hs_T_1 S12.18hs_T_1
## -2.512300e-01 -1.899232e-04 -1.528885e-01
## S13.18hs_T_1 S17.18hs_T_1 S18.18hs_T_1
## -3.666922e-01 3.354491e-02 -6.985800e-01
## S19.18hs_T_1 S1.18hs_T_1 S2.18hs_T_1
## 1.086932e-01 1.082309e+00 -6.829105e-01
## S3.18hs_T_1 S4.18hs_T_1 S5.18hs_T_1
## -1.937045e+00 4.737713e-01 -5.200266e-01
## S6.18hs_T_1 S7.18hs_T_1 S8.18hs_T_1
## -2.023516e-01 2.607823e+00 1.337250e-01
## Est.humedad_min_T_1 Est.humedad_med_T_1 Est.humedad_max_T_1
## 5.398319e-01 -1.169272e-01 -4.693922e-01
## Est.temp_min_T_1 Est.temp_max_T_1 Est.temp_med_T_1
## 6.337837e+00 6.721672e+00 -1.321470e+01
## Standard deviation of the residuals: 7.090707e-08
##
## $S3.min_t
##
## Parameters of node S3.min_t (Gaussian distribution)
##
## Conditional density: S3.min_t | S11.max_T_2 + S13.max_T_2 + S3.max_T_2 + S12.media_T_2 + S20.media_T_2 + S3.media_T_2 + S4.media_T_2 + S6.media_T_2 + S1.min_T_2 + S2.min_T_2 + S3.min_T_2 + S8.min_T_2 + S13.15hs_T_2 + S17.15hs_T_2 + S3.15hs_T_2 + S5.15hs_T_2 + S19.12hs_T_2 + S3.12hs_T_2 + S10.18hs_T_2 + S14.18hs_T_2 + S2.18hs_T_2 + S3.18hs_T_2 + S4.18hs_T_2 + Est.temp_min_T_2 + S2.max_T_1 + S3.max_T_1 + S13.media_T_1 + S19.media_T_1 + S3.media_T_1 + S4.media_T_1 + S5.media_T_1 + S9.media_T_1 + S12.min_T_1 + S13.min_T_1 + S3.min_T_1 + S17.15hs_T_1 + S1.15hs_T_1 + S3.15hs_T_1 + S3.12hs_T_1 + S12.18hs_T_1 + S3.18hs_T_1 + Est.humedad_min_T_1
## Coefficients:
## (Intercept) S11.max_T_2 S13.max_T_2
## -9.22155198 -0.54349741 1.20033842
## S3.max_T_2 S12.media_T_2 S20.media_T_2
## -0.45952530 -5.28584717 3.61328124
## S3.media_T_2 S4.media_T_2 S6.media_T_2
## -7.47183422 1.94735806 6.91786530
## S1.min_T_2 S2.min_T_2 S3.min_T_2
## -1.04537532 -1.22325389 0.96865077
## S8.min_T_2 S13.15hs_T_2 S17.15hs_T_2
## 1.46109411 0.95887664 -0.75376586
## S3.15hs_T_2 S5.15hs_T_2 S19.12hs_T_2
## 1.58582923 -1.68504164 -1.00661665
## S3.12hs_T_2 S10.18hs_T_2 S14.18hs_T_2
## 0.78361405 -2.12452782 1.92673271
## S2.18hs_T_2 S3.18hs_T_2 S4.18hs_T_2
## 0.75291121 1.03404164 -1.46469817
## Est.temp_min_T_2 S2.max_T_1 S3.max_T_1
## 0.19227288 1.08711936 -1.54483932
## S13.media_T_1 S19.media_T_1 S3.media_T_1
## -4.22514139 3.18954889 5.97002092
## S4.media_T_1 S5.media_T_1 S9.media_T_1
## 4.69381028 -4.12056273 -5.52521028
## S12.min_T_1 S13.min_T_1 S3.min_T_1
## 1.52611458 -0.92404551 -0.22854634
## S17.15hs_T_1 S1.15hs_T_1 S3.15hs_T_1
## -0.97420690 0.63030764 0.94121588
## S3.12hs_T_1 S12.18hs_T_1 S3.18hs_T_1
## 0.12337071 1.30184733 -1.21662096
## Est.humedad_min_T_1
## 0.04285554
## Standard deviation of the residuals: 1.143421
##
## $S4.min_t
##
## Parameters of node S4.min_t (Gaussian distribution)
##
## Conditional density: S4.min_t | S11.max_T_2 + S12.max_T_2 + S14.max_T_2 + S16.max_T_2 + S17.max_T_2 + S18.max_T_2 + S20.max_T_2 + S2.max_T_2 + S3.max_T_2 + S4.max_T_2 + S5.max_T_2 + S6.max_T_2 + S11.media_T_2 + S13.media_T_2 + S14.media_T_2 + S15.media_T_2 + S17.media_T_2 + S1.media_T_2 + S20.media_T_2 + S2.media_T_2 + S3.media_T_2 + S4.media_T_2 + S7.media_T_2 + S11.min_T_2 + S12.min_T_2 + S14.min_T_2 + S16.min_T_2 + S18.min_T_2 + S19.min_T_2 + S20.min_T_2 + S2.min_T_2 + S4.min_T_2 + S5.min_T_2 + S6.min_T_2 + S7.min_T_2 + S9.min_T_2 + S10.15hs_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S14.15hs_T_2 + S15.15hs_T_2 + S16.15hs_T_2 + S17.15hs_T_2 + S18.15hs_T_2 + S19.15hs_T_2 + S3.15hs_T_2 + S4.15hs_T_2 + S5.15hs_T_2 + S6.15hs_T_2 + S7.15hs_T_2 + S8.15hs_T_2 + S10.12hs_T_2 + S11.12hs_T_2 + S12.12hs_T_2 + S15.12hs_T_2 + S18.12hs_T_2 + S19.12hs_T_2 + S1.12hs_T_2 + S3.12hs_T_2 + S4.12hs_T_2 + S5.12hs_T_2 + S6.12hs_T_2 + S7.12hs_T_2 + S8.12hs_T_2 + S9.12hs_T_2 + S10.18hs_T_2 + S11.18hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S17.18hs_T_2 + S18.18hs_T_2 + S1.18hs_T_2 + S3.18hs_T_2 + S4.18hs_T_2 + S5.18hs_T_2 + S6.18hs_T_2 + S7.18hs_T_2 + S8.18hs_T_2 + S9.18hs_T_2 + Est.humedad_min_T_2 + Est.humedad_med_T_2 + Est.temp_min_T_2 + S11.max_T_1 + S12.max_T_1 + S13.max_T_1 + S14.max_T_1 + S15.max_T_1 + S16.max_T_1 + S17.max_T_1 + S1.max_T_1 + S20.max_T_1 + S2.max_T_1 + S3.max_T_1 + S4.max_T_1 + S5.max_T_1 + S6.max_T_1 + S7.max_T_1 + S8.max_T_1 + S9.max_T_1 + S10.media_T_1 + S11.media_T_1 + S12.media_T_1 + S13.media_T_1 + S14.media_T_1 + S15.media_T_1 + S17.media_T_1 + S18.media_T_1 + S1.media_T_1 + S20.media_T_1 + S3.media_T_1 + S4.media_T_1 + S5.media_T_1 + S6.media_T_1 + S7.media_T_1 + S8.media_T_1 + S9.media_T_1 + S10.min_T_1 + S11.min_T_1 + S12.min_T_1 + S13.min_T_1 + S14.min_T_1 + S17.min_T_1 + S18.min_T_1 + S19.min_T_1 + S1.min_T_1 + S2.min_T_1 + S4.min_T_1 + S5.min_T_1 + S6.min_T_1 + S7.min_T_1 + S8.min_T_1 + S9.min_T_1 + S10.15hs_T_1 + S11.15hs_T_1 + S13.15hs_T_1 + S14.15hs_T_1 + S15.15hs_T_1 + S16.15hs_T_1 + S18.15hs_T_1 + S1.15hs_T_1 + S20.15hs_T_1 + S2.15hs_T_1 + S3.15hs_T_1 + S4.15hs_T_1 + S5.15hs_T_1 + S6.15hs_T_1 + S8.15hs_T_1 + S10.12hs_T_1 + S11.12hs_T_1 + S12.12hs_T_1 + S14.12hs_T_1 + S15.12hs_T_1 + S19.12hs_T_1 + S1.12hs_T_1 + S20.12hs_T_1 + S4.12hs_T_1 + S5.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S9.12hs_T_1 + S10.18hs_T_1 + S11.18hs_T_1 + S13.18hs_T_1 + S14.18hs_T_1 + S19.18hs_T_1 + S20.18hs_T_1 + S2.18hs_T_1 + S3.18hs_T_1 + S4.18hs_T_1 + S5.18hs_T_1 + S6.18hs_T_1 + S7.18hs_T_1 + S8.18hs_T_1 + S9.18hs_T_1 + Est.temp_max_T_1
## Coefficients:
## (Intercept) S11.max_T_2 S12.max_T_2
## -9.301462e+00 5.258590e-05 -6.707992e-02
## S14.max_T_2 S16.max_T_2 S17.max_T_2
## 2.433200e+00 -1.257907e-02 7.032097e-01
## S18.max_T_2 S20.max_T_2 S2.max_T_2
## 7.366219e-01 -4.140639e-01 -6.631356e-01
## S3.max_T_2 S4.max_T_2 S5.max_T_2
## 1.171354e-02 1.458183e+00 -4.139439e+00
## S6.max_T_2 S11.media_T_2 S13.media_T_2
## -3.281307e-01 -8.155203e+00 -7.053176e+00
## S14.media_T_2 S15.media_T_2 S17.media_T_2
## -1.085301e+01 1.854260e+00 2.054053e+00
## S1.media_T_2 S20.media_T_2 S2.media_T_2
## 8.129627e-01 1.062430e+01 3.271298e+00
## S3.media_T_2 S4.media_T_2 S7.media_T_2
## 3.238195e+00 4.584271e+00 1.100259e-01
## S11.min_T_2 S12.min_T_2 S14.min_T_2
## -1.736925e+00 -1.867279e-01 -4.341436e-01
## S16.min_T_2 S18.min_T_2 S19.min_T_2
## 1.619542e+00 1.114482e+00 -2.231879e+00
## S20.min_T_2 S2.min_T_2 S4.min_T_2
## 5.586007e-01 -2.114532e+00 3.823277e+00
## S5.min_T_2 S6.min_T_2 S7.min_T_2
## 2.729638e-01 -5.095157e-01 -3.921600e-01
## S9.min_T_2 S10.15hs_T_2 S12.15hs_T_2
## 1.654750e-01 7.605477e-01 3.105500e-01
## S13.15hs_T_2 S14.15hs_T_2 S15.15hs_T_2
## 4.242209e+00 -1.526027e+00 -3.153653e+00
## S16.15hs_T_2 S17.15hs_T_2 S18.15hs_T_2
## 1.425300e+00 -2.398920e+00 1.501193e+00
## S19.15hs_T_2 S3.15hs_T_2 S4.15hs_T_2
## 1.114666e+00 -2.646416e+00 -1.612287e-01
## S5.15hs_T_2 S6.15hs_T_2 S7.15hs_T_2
## -8.591273e-01 2.653074e+00 -6.969104e-01
## S8.15hs_T_2 S10.12hs_T_2 S11.12hs_T_2
## -4.875497e-01 -1.576444e+00 -4.922391e-01
## S12.12hs_T_2 S15.12hs_T_2 S18.12hs_T_2
## -2.686451e+00 2.292691e+00 -3.621261e+00
## S19.12hs_T_2 S1.12hs_T_2 S3.12hs_T_2
## 2.288009e+00 -1.345766e+00 -3.744679e-04
## S4.12hs_T_2 S5.12hs_T_2 S6.12hs_T_2
## -1.951181e-01 2.867301e+00 9.383103e-01
## S7.12hs_T_2 S8.12hs_T_2 S9.12hs_T_2
## -1.824670e+00 1.022198e+00 2.283686e+00
## S10.18hs_T_2 S11.18hs_T_2 S14.18hs_T_2
## -4.615847e+00 1.608600e+00 4.604222e+00
## S15.18hs_T_2 S17.18hs_T_2 S18.18hs_T_2
## 4.357201e-01 1.532668e+00 -1.043157e+00
## S1.18hs_T_2 S3.18hs_T_2 S4.18hs_T_2
## -1.359047e+00 2.715207e-02 -2.207564e+00
## S5.18hs_T_2 S6.18hs_T_2 S7.18hs_T_2
## 8.097388e-01 -1.155788e+00 1.025309e+00
## S8.18hs_T_2 S9.18hs_T_2 Est.humedad_min_T_2
## -4.411721e-01 8.665463e-01 -2.811798e-01
## Est.humedad_med_T_2 Est.temp_min_T_2 S11.max_T_1
## 3.186539e-01 1.193324e-01 -1.221886e-01
## S12.max_T_1 S13.max_T_1 S14.max_T_1
## 2.320593e-01 -9.385541e-01 1.360939e+00
## S15.max_T_1 S16.max_T_1 S17.max_T_1
## -6.932825e-01 8.301454e-02 -3.430368e-01
## S1.max_T_1 S20.max_T_1 S2.max_T_1
## 5.296785e-02 9.121375e-01 1.533989e-01
## S3.max_T_1 S4.max_T_1 S5.max_T_1
## -2.230328e+00 -6.584605e-01 9.427425e-01
## S6.max_T_1 S7.max_T_1 S8.max_T_1
## -3.290661e-03 4.401443e-03 2.186298e+00
## S9.max_T_1 S10.media_T_1 S11.media_T_1
## -2.185792e+00 7.523757e+00 4.435446e-03
## S12.media_T_1 S13.media_T_1 S14.media_T_1
## 7.251967e+00 1.027455e+00 1.886405e+00
## S15.media_T_1 S17.media_T_1 S18.media_T_1
## 1.315312e+00 -2.403056e+00 -4.627782e+00
## S1.media_T_1 S20.media_T_1 S3.media_T_1
## 7.505744e+00 -7.221660e+00 -2.635062e-01
## S4.media_T_1 S5.media_T_1 S6.media_T_1
## 8.021960e+00 -1.951105e+01 1.276176e+00
## S7.media_T_1 S8.media_T_1 S9.media_T_1
## -4.736273e+00 1.424612e+00 9.162676e-01
## S10.min_T_1 S11.min_T_1 S12.min_T_1
## 1.613969e+00 9.054074e-01 2.262794e+00
## S13.min_T_1 S14.min_T_1 S17.min_T_1
## -5.652836e-01 -5.222865e+00 -1.373329e+00
## S18.min_T_1 S19.min_T_1 S1.min_T_1
## 1.344784e-01 3.028691e+00 -1.808742e+00
## S2.min_T_1 S4.min_T_1 S5.min_T_1
## 8.801447e-01 -1.461550e+00 -1.514839e+00
## S6.min_T_1 S7.min_T_1 S8.min_T_1
## 4.702599e+00 -1.309372e+00 9.671634e-01
## S9.min_T_1 S10.15hs_T_1 S11.15hs_T_1
## -6.411163e-01 -3.928263e+00 -1.046188e+00
## S13.15hs_T_1 S14.15hs_T_1 S15.15hs_T_1
## -4.330518e-01 2.376173e+00 -7.294882e-01
## S16.15hs_T_1 S18.15hs_T_1 S1.15hs_T_1
## -2.998933e-01 6.929277e-02 1.531966e+00
## S20.15hs_T_1 S2.15hs_T_1 S3.15hs_T_1
## 1.303411e+00 -4.787153e+00 3.048927e+00
## S4.15hs_T_1 S5.15hs_T_1 S6.15hs_T_1
## -2.608811e-01 -2.311001e-01 2.041695e+00
## S8.15hs_T_1 S10.12hs_T_1 S11.12hs_T_1
## 2.373093e+00 7.973831e-01 1.205446e+00
## S12.12hs_T_1 S14.12hs_T_1 S15.12hs_T_1
## -1.663329e+00 -1.924443e-01 1.044457e-01
## S19.12hs_T_1 S1.12hs_T_1 S20.12hs_T_1
## 1.214872e+00 -2.387994e+00 2.627425e+00
## S4.12hs_T_1 S5.12hs_T_1 S6.12hs_T_1
## -6.058827e-01 3.175972e+00 -1.874583e+00
## S7.12hs_T_1 S8.12hs_T_1 S9.12hs_T_1
## 1.289984e+00 -2.624140e+00 -4.525260e-02
## S10.18hs_T_1 S11.18hs_T_1 S13.18hs_T_1
## -6.230916e-01 -1.642740e+00 1.846625e+00
## S14.18hs_T_1 S19.18hs_T_1 S20.18hs_T_1
## -2.535348e+00 -3.077900e-01 2.538166e+00
## S2.18hs_T_1 S3.18hs_T_1 S4.18hs_T_1
## -1.647833e+00 -5.525313e-03 1.910992e+00
## S5.18hs_T_1 S6.18hs_T_1 S7.18hs_T_1
## 6.545324e-01 2.559227e+00 -8.902478e-01
## S8.18hs_T_1 S9.18hs_T_1 Est.temp_max_T_1
## -8.750729e-01 -9.250585e-01 -5.706507e-02
## Standard deviation of the residuals: 1.218142e-07
##
## $S5.min_t
##
## Parameters of node S5.min_t (Gaussian distribution)
##
## Conditional density: S5.min_t | S10.max_T_2 + S16.max_T_2 + S18.max_T_2 + S20.max_T_2 + S3.max_T_2 + S5.max_T_2 + S12.media_T_2 + S18.media_T_2 + S4.media_T_2 + S5.media_T_2 + S8.media_T_2 + S12.min_T_2 + S16.min_T_2 + S5.min_T_2 + S13.15hs_T_2 + S17.15hs_T_2 + S5.15hs_T_2 + S6.15hs_T_2 + S1.12hs_T_2 + S5.12hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S5.18hs_T_2 + S9.18hs_T_2 + S13.max_T_1 + S2.max_T_1 + S5.max_T_1 + S9.max_T_1 + S5.media_T_1 + S8.media_T_1 + S9.media_T_1 + S12.min_T_1 + S14.min_T_1 + S5.min_T_1 + S6.min_T_1 + S8.min_T_1 + S5.15hs_T_1 + S12.12hs_T_1 + S4.12hs_T_1 + S5.12hs_T_1 + S8.12hs_T_1 + S5.18hs_T_1 + Est.humedad_min_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S10.max_T_2 S16.max_T_2
## -5.61548536 -0.85986451 0.78289588
## S18.max_T_2 S20.max_T_2 S3.max_T_2
## 0.62544095 0.85582397 -0.56256779
## S5.max_T_2 S12.media_T_2 S18.media_T_2
## -0.80985568 -4.90400044 -5.20300547
## S4.media_T_2 S5.media_T_2 S8.media_T_2
## 6.19293263 -0.14913885 3.88599397
## S12.min_T_2 S16.min_T_2 S5.min_T_2
## 2.11928351 -2.18258276 0.26947278
## S13.15hs_T_2 S17.15hs_T_2 S5.15hs_T_2
## 1.49646998 -0.94002692 -1.99701888
## S6.15hs_T_2 S1.12hs_T_2 S5.12hs_T_2
## 1.53040177 -0.63191414 0.62081867
## S14.18hs_T_2 S15.18hs_T_2 S5.18hs_T_2
## 2.05990861 0.74209215 -0.87743149
## S9.18hs_T_2 S13.max_T_1 S2.max_T_1
## -1.80150407 -0.62729459 1.41277173
## S5.max_T_1 S9.max_T_1 S5.media_T_1
## 0.06059778 -0.85942508 -1.34131432
## S8.media_T_1 S9.media_T_1 S12.min_T_1
## 5.30925417 -3.98521772 1.46897087
## S14.min_T_1 S5.min_T_1 S6.min_T_1
## -1.16440181 -1.31438762 1.96932060
## S8.min_T_1 S5.15hs_T_1 S12.12hs_T_1
## -0.65630161 0.43318705 -0.55105601
## S4.12hs_T_1 S5.12hs_T_1 S8.12hs_T_1
## 1.36455152 -0.31947808 -0.50793060
## S5.18hs_T_1 Est.humedad_min_T_1 Est.temp_min_T_1
## -0.02713827 0.03913640 0.09122811
## Standard deviation of the residuals: 1.126593
##
## $S6.min_t
##
## Parameters of node S6.min_t (Gaussian distribution)
##
## Conditional density: S6.min_t | S10.max_T_2 + S11.max_T_2 + S12.max_T_2 + S13.max_T_2 + S14.max_T_2 + S16.max_T_2 + S17.max_T_2 + S19.max_T_2 + S1.max_T_2 + S20.max_T_2 + S2.max_T_2 + S5.max_T_2 + S6.max_T_2 + S7.max_T_2 + S9.max_T_2 + S12.media_T_2 + S13.media_T_2 + S16.media_T_2 + S17.media_T_2 + S18.media_T_2 + S20.media_T_2 + S2.media_T_2 + S4.media_T_2 + S5.media_T_2 + S6.media_T_2 + S7.media_T_2 + S8.media_T_2 + S9.media_T_2 + S10.min_T_2 + S11.min_T_2 + S13.min_T_2 + S14.min_T_2 + S16.min_T_2 + S17.min_T_2 + S18.min_T_2 + S1.min_T_2 + S2.min_T_2 + S4.min_T_2 + S5.min_T_2 + S6.min_T_2 + S7.min_T_2 + S8.min_T_2 + S9.min_T_2 + S10.15hs_T_2 + S11.15hs_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S14.15hs_T_2 + S17.15hs_T_2 + S18.15hs_T_2 + S19.15hs_T_2 + S20.15hs_T_2 + S2.15hs_T_2 + S3.15hs_T_2 + S4.15hs_T_2 + S5.15hs_T_2 + S6.15hs_T_2 + S8.15hs_T_2 + S10.12hs_T_2 + S13.12hs_T_2 + S14.12hs_T_2 + S16.12hs_T_2 + S17.12hs_T_2 + S18.12hs_T_2 + S1.12hs_T_2 + S20.12hs_T_2 + S2.12hs_T_2 + S3.12hs_T_2 + S5.12hs_T_2 + S6.12hs_T_2 + S7.12hs_T_2 + S8.12hs_T_2 + S9.12hs_T_2 + S10.18hs_T_2 + S12.18hs_T_2 + S13.18hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S17.18hs_T_2 + S1.18hs_T_2 + S20.18hs_T_2 + S2.18hs_T_2 + S3.18hs_T_2 + S4.18hs_T_2 + S5.18hs_T_2 + S6.18hs_T_2 + S7.18hs_T_2 + S8.18hs_T_2 + S9.18hs_T_2 + Est.humedad_min_T_2 + Est.humedad_med_T_2 + Est.humedad_max_T_2 + S10.max_T_1 + S11.max_T_1 + S12.max_T_1 + S13.max_T_1 + S14.max_T_1 + S15.max_T_1 + S16.max_T_1 + S17.max_T_1 + S19.max_T_1 + S20.max_T_1 + S2.max_T_1 + S3.max_T_1 + S4.max_T_1 + S5.max_T_1 + S6.max_T_1 + S7.max_T_1 + S8.max_T_1 + S9.max_T_1 + S10.media_T_1 + S11.media_T_1 + S15.media_T_1 + S18.media_T_1 + S1.media_T_1 + S20.media_T_1 + S2.media_T_1 + S3.media_T_1 + S4.media_T_1 + S5.media_T_1 + S6.media_T_1 + S7.media_T_1 + S8.media_T_1 + S12.min_T_1 + S13.min_T_1 + S15.min_T_1 + S16.min_T_1 + S18.min_T_1 + S19.min_T_1 + S1.min_T_1 + S20.min_T_1 + S2.min_T_1 + S3.min_T_1 + S4.min_T_1 + S5.min_T_1 + S6.min_T_1 + S7.min_T_1 + S8.min_T_1 + S10.15hs_T_1 + S11.15hs_T_1 + S14.15hs_T_1 + S16.15hs_T_1 + S19.15hs_T_1 + S20.15hs_T_1 + S2.15hs_T_1 + S3.15hs_T_1 + S4.15hs_T_1 + S5.15hs_T_1 + S6.15hs_T_1 + S10.12hs_T_1 + S12.12hs_T_1 + S17.12hs_T_1 + S18.12hs_T_1 + S1.12hs_T_1 + S20.12hs_T_1 + S2.12hs_T_1 + S3.12hs_T_1 + S4.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S11.18hs_T_1 + S14.18hs_T_1 + S19.18hs_T_1 + S1.18hs_T_1 + S20.18hs_T_1 + S2.18hs_T_1 + S3.18hs_T_1 + S4.18hs_T_1 + S5.18hs_T_1 + S6.18hs_T_1 + S7.18hs_T_1 + S8.18hs_T_1 + Est.humedad_min_T_1 + Est.humedad_med_T_1 + Est.temp_min_T_1
## Coefficients:
## (Intercept) S10.max_T_2 S11.max_T_2
## -3.043949120 -0.618635152 0.771292532
## S12.max_T_2 S13.max_T_2 S14.max_T_2
## -0.112374129 -0.126123896 1.371968543
## S16.max_T_2 S17.max_T_2 S19.max_T_2
## 1.308827080 -1.206082903 -0.606453808
## S1.max_T_2 S20.max_T_2 S2.max_T_2
## 0.339204507 0.881247908 -1.814115952
## S5.max_T_2 S6.max_T_2 S7.max_T_2
## -1.724168213 0.586165791 1.478118752
## S9.max_T_2 S12.media_T_2 S13.media_T_2
## 0.712013919 0.834965773 -3.281783518
## S16.media_T_2 S17.media_T_2 S18.media_T_2
## -4.735877680 -1.600615170 -8.877691165
## S20.media_T_2 S2.media_T_2 S4.media_T_2
## -0.002221312 -0.322480785 7.944833318
## S5.media_T_2 S6.media_T_2 S7.media_T_2
## 9.508614200 -0.840902276 -0.578040241
## S8.media_T_2 S9.media_T_2 S10.min_T_2
## -0.011536355 0.686242283 -2.095923425
## S11.min_T_2 S13.min_T_2 S14.min_T_2
## -0.652800416 1.450118987 1.872688282
## S16.min_T_2 S17.min_T_2 S18.min_T_2
## -0.895530136 0.918080363 -0.287770891
## S1.min_T_2 S2.min_T_2 S4.min_T_2
## -0.450206869 -2.620723793 2.272743926
## S5.min_T_2 S6.min_T_2 S7.min_T_2
## 2.414892592 1.302703890 0.537190863
## S8.min_T_2 S9.min_T_2 S10.15hs_T_2
## 0.267525981 -3.233503009 0.157006544
## S11.15hs_T_2 S12.15hs_T_2 S13.15hs_T_2
## 0.303960251 -2.401453560 4.387889791
## S14.15hs_T_2 S17.15hs_T_2 S18.15hs_T_2
## -2.101659158 -0.990427851 3.812597922
## S19.15hs_T_2 S20.15hs_T_2 S2.15hs_T_2
## 0.968399100 -2.181818222 2.816476402
## S3.15hs_T_2 S4.15hs_T_2 S5.15hs_T_2
## 0.120964503 0.375811148 -6.573699894
## S6.15hs_T_2 S8.15hs_T_2 S10.12hs_T_2
## 2.383579898 -1.544560686 -1.425100232
## S13.12hs_T_2 S14.12hs_T_2 S16.12hs_T_2
## -1.118048289 -1.161019066 1.158602693
## S17.12hs_T_2 S18.12hs_T_2 S1.12hs_T_2
## 0.091246253 0.385616530 -0.760513821
## S20.12hs_T_2 S2.12hs_T_2 S3.12hs_T_2
## -2.255363497 -1.561223315 0.264613296
## S5.12hs_T_2 S6.12hs_T_2 S7.12hs_T_2
## 2.639964274 0.109903445 -1.166274773
## S8.12hs_T_2 S9.12hs_T_2 S10.18hs_T_2
## 3.585595340 1.130580103 -2.484141393
## S12.18hs_T_2 S13.18hs_T_2 S14.18hs_T_2
## 2.060035321 -3.875650929 3.980627865
## S15.18hs_T_2 S17.18hs_T_2 S1.18hs_T_2
## 1.359342882 0.475381671 -1.173146488
## S20.18hs_T_2 S2.18hs_T_2 S3.18hs_T_2
## 3.480609774 0.630430642 0.285957120
## S4.18hs_T_2 S5.18hs_T_2 S6.18hs_T_2
## -1.930010304 -0.054911772 0.319648270
## S7.18hs_T_2 S8.18hs_T_2 S9.18hs_T_2
## -1.702456802 -0.044650802 -1.379387192
## Est.humedad_min_T_2 Est.humedad_med_T_2 Est.humedad_max_T_2
## -0.001273634 -0.472998732 0.488045883
## S10.max_T_1 S11.max_T_1 S12.max_T_1
## 0.385814186 1.719994968 -0.921960942
## S13.max_T_1 S14.max_T_1 S15.max_T_1
## 0.820345545 2.554878485 -1.485897898
## S16.max_T_1 S17.max_T_1 S19.max_T_1
## 0.012237684 -1.270390729 -1.459955593
## S20.max_T_1 S2.max_T_1 S3.max_T_1
## 0.265757204 0.131420069 -0.915380082
## S4.max_T_1 S5.max_T_1 S6.max_T_1
## 0.181483707 -0.656551379 -0.520678362
## S7.max_T_1 S8.max_T_1 S9.max_T_1
## 0.477774083 2.766108458 -1.723915774
## S10.media_T_1 S11.media_T_1 S15.media_T_1
## -1.093647197 -2.466184060 0.048752764
## S18.media_T_1 S1.media_T_1 S20.media_T_1
## 3.228586183 9.440279610 -2.099565158
## S2.media_T_1 S3.media_T_1 S4.media_T_1
## 3.595030966 6.709339766 3.674838382
## S5.media_T_1 S6.media_T_1 S7.media_T_1
## -12.136997009 -5.050129174 -3.605049692
## S8.media_T_1 S12.min_T_1 S13.min_T_1
## -0.079446433 2.709469205 4.613281353
## S15.min_T_1 S16.min_T_1 S18.min_T_1
## -0.742086819 -1.271933899 -1.846910377
## S19.min_T_1 S1.min_T_1 S20.min_T_1
## 0.050165870 1.309667230 1.172825723
## S2.min_T_1 S3.min_T_1 S4.min_T_1
## -2.954403247 0.787334127 -0.166288013
## S5.min_T_1 S6.min_T_1 S7.min_T_1
## -1.715708615 -0.900873800 0.767020487
## S8.min_T_1 S10.15hs_T_1 S11.15hs_T_1
## -1.067269449 -1.531468136 -2.926558414
## S14.15hs_T_1 S16.15hs_T_1 S19.15hs_T_1
## -0.477550099 -0.014445017 0.212008308
## S20.15hs_T_1 S2.15hs_T_1 S3.15hs_T_1
## 2.486687787 -1.945867799 1.311777952
## S4.15hs_T_1 S5.15hs_T_1 S6.15hs_T_1
## -2.069163765 3.294579569 2.091534212
## S10.12hs_T_1 S12.12hs_T_1 S17.12hs_T_1
## 2.006239754 -1.804304797 -0.389909382
## S18.12hs_T_1 S1.12hs_T_1 S20.12hs_T_1
## 0.006144064 -0.355712731 0.038034800
## S2.12hs_T_1 S3.12hs_T_1 S4.12hs_T_1
## 0.921305997 -0.138209895 0.657576269
## S6.12hs_T_1 S7.12hs_T_1 S8.12hs_T_1
## -1.527023719 2.576724066 -2.216048222
## S11.18hs_T_1 S14.18hs_T_1 S19.18hs_T_1
## 1.546645821 -1.210413725 0.518834393
## S1.18hs_T_1 S20.18hs_T_1 S2.18hs_T_1
## -4.864667919 -0.149005159 -0.532082194
## S3.18hs_T_1 S4.18hs_T_1 S5.18hs_T_1
## -0.506191011 1.533093703 0.263080079
## S6.18hs_T_1 S7.18hs_T_1 S8.18hs_T_1
## 1.833597273 -0.689146668 1.637605253
## Est.humedad_min_T_1 Est.humedad_med_T_1 Est.temp_min_T_1
## 0.962968396 -0.936943187 0.002617881
## Standard deviation of the residuals: 7.812063e-08
##
## $S7.min_t
##
## Parameters of node S7.min_t (Gaussian distribution)
##
## Conditional density: S7.min_t | S11.max_T_2 + S14.max_T_2 + S20.max_T_2 + S7.max_T_2 + S10.media_T_2 + S12.media_T_2 + S17.media_T_2 + S6.media_T_2 + S7.media_T_2 + S7.min_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S17.15hs_T_2 + S5.15hs_T_2 + S7.15hs_T_2 + S4.12hs_T_2 + S7.12hs_T_2 + S12.18hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S1.18hs_T_2 + S7.18hs_T_2 + Est.temp_min_T_2 + S13.max_T_1 + S2.max_T_1 + S3.max_T_1 + S7.max_T_1 + S13.media_T_1 + S3.media_T_1 + S7.media_T_1 + S8.media_T_1 + S9.media_T_1 + S7.min_T_1 + S12.15hs_T_1 + S3.15hs_T_1 + S7.15hs_T_1 + S2.12hs_T_1 + S4.12hs_T_1 + S7.12hs_T_1 + S12.18hs_T_1 + S7.18hs_T_1 + Est.humedad_min_T_1
## Coefficients:
## (Intercept) S11.max_T_2 S14.max_T_2
## -10.47693896 -0.87853852 0.75055909
## S20.max_T_2 S7.max_T_2 S10.media_T_2
## 1.07709188 -0.81980760 -4.60891612
## S12.media_T_2 S17.media_T_2 S6.media_T_2
## -3.46467112 -2.55046769 3.56055965
## S7.media_T_2 S7.min_T_2 S12.15hs_T_2
## 6.88762898 0.09362714 -0.71996245
## S13.15hs_T_2 S17.15hs_T_2 S5.15hs_T_2
## 2.33793098 -0.58266236 -1.26576273
## S7.15hs_T_2 S4.12hs_T_2 S7.12hs_T_2
## 0.16348350 0.58231198 -0.68021978
## S12.18hs_T_2 S14.18hs_T_2 S15.18hs_T_2
## 0.77119797 1.01087313 0.75841967
## S1.18hs_T_2 S7.18hs_T_2 Est.temp_min_T_2
## -1.43665924 -0.92916993 0.22022633
## S13.max_T_1 S2.max_T_1 S3.max_T_1
## -1.03042572 1.54173365 -1.18335248
## S7.max_T_1 S13.media_T_1 S3.media_T_1
## 0.47519073 -2.87170410 2.87569808
## S7.media_T_1 S8.media_T_1 S9.media_T_1
## -0.11395687 4.66941147 -4.46179782
## S7.min_T_1 S12.15hs_T_1 S3.15hs_T_1
## 0.27725828 -1.13171304 0.89320284
## S7.15hs_T_1 S2.12hs_T_1 S4.12hs_T_1
## 0.51781438 -1.10774235 1.30177791
## S7.12hs_T_1 S12.18hs_T_1 S7.18hs_T_1
## -0.08329833 1.15892460 -1.01383911
## Est.humedad_min_T_1
## 0.05840135
## Standard deviation of the residuals: 1.231158
##
## $S8.min_t
##
## Parameters of node S8.min_t (Gaussian distribution)
##
## Conditional density: S8.min_t | S11.max_T_2 + S13.max_T_2 + S14.max_T_2 + S15.max_T_2 + S16.max_T_2 + S1.max_T_2 + S20.max_T_2 + S2.max_T_2 + S3.max_T_2 + S5.max_T_2 + S6.max_T_2 + S7.max_T_2 + S8.max_T_2 + S9.max_T_2 + S10.media_T_2 + S11.media_T_2 + S13.media_T_2 + S14.media_T_2 + S15.media_T_2 + S16.media_T_2 + S17.media_T_2 + S19.media_T_2 + S20.media_T_2 + S2.media_T_2 + S3.media_T_2 + S4.media_T_2 + S5.media_T_2 + S6.media_T_2 + S7.media_T_2 + S8.media_T_2 + S9.media_T_2 + S12.min_T_2 + S14.min_T_2 + S16.min_T_2 + S18.min_T_2 + S19.min_T_2 + S1.min_T_2 + S20.min_T_2 + S2.min_T_2 + S3.min_T_2 + S4.min_T_2 + S5.min_T_2 + S6.min_T_2 + S8.min_T_2 + S9.min_T_2 + S10.15hs_T_2 + S11.15hs_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S14.15hs_T_2 + S17.15hs_T_2 + S18.15hs_T_2 + S19.15hs_T_2 + S20.15hs_T_2 + S2.15hs_T_2 + S4.15hs_T_2 + S5.15hs_T_2 + S6.15hs_T_2 + S7.15hs_T_2 + S8.15hs_T_2 + S9.15hs_T_2 + S10.12hs_T_2 + S12.12hs_T_2 + S13.12hs_T_2 + S14.12hs_T_2 + S15.12hs_T_2 + S17.12hs_T_2 + S18.12hs_T_2 + S20.12hs_T_2 + S3.12hs_T_2 + S5.12hs_T_2 + S6.12hs_T_2 + S7.12hs_T_2 + S8.12hs_T_2 + S9.12hs_T_2 + S10.18hs_T_2 + S11.18hs_T_2 + S12.18hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S16.18hs_T_2 + S18.18hs_T_2 + S1.18hs_T_2 + S20.18hs_T_2 + S2.18hs_T_2 + S3.18hs_T_2 + S4.18hs_T_2 + S5.18hs_T_2 + S6.18hs_T_2 + S7.18hs_T_2 + S8.18hs_T_2 + S9.18hs_T_2 + Est.temp_max_T_2 + S12.max_T_1 + S14.max_T_1 + S15.max_T_1 + S17.max_T_1 + S18.max_T_1 + S1.max_T_1 + S2.max_T_1 + S3.max_T_1 + S4.max_T_1 + S6.max_T_1 + S7.max_T_1 + S8.max_T_1 + S9.max_T_1 + S10.media_T_1 + S11.media_T_1 + S13.media_T_1 + S14.media_T_1 + S15.media_T_1 + S16.media_T_1 + S17.media_T_1 + S19.media_T_1 + S20.media_T_1 + S3.media_T_1 + S4.media_T_1 + S5.media_T_1 + S6.media_T_1 + S7.media_T_1 + S8.media_T_1 + S9.media_T_1 + S10.min_T_1 + S11.min_T_1 + S12.min_T_1 + S13.min_T_1 + S14.min_T_1 + S15.min_T_1 + S16.min_T_1 + S17.min_T_1 + S18.min_T_1 + S19.min_T_1 + S1.min_T_1 + S3.min_T_1 + S8.min_T_1 + S10.15hs_T_1 + S11.15hs_T_1 + S12.15hs_T_1 + S13.15hs_T_1 + S14.15hs_T_1 + S15.15hs_T_1 + S1.15hs_T_1 + S20.15hs_T_1 + S2.15hs_T_1 + S3.15hs_T_1 + S7.15hs_T_1 + S8.15hs_T_1 + S9.15hs_T_1 + S10.12hs_T_1 + S11.12hs_T_1 + S12.12hs_T_1 + S14.12hs_T_1 + S15.12hs_T_1 + S16.12hs_T_1 + S19.12hs_T_1 + S20.12hs_T_1 + S3.12hs_T_1 + S4.12hs_T_1 + S5.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S10.18hs_T_1 + S12.18hs_T_1 + S16.18hs_T_1 + S17.18hs_T_1 + S19.18hs_T_1 + S20.18hs_T_1 + S2.18hs_T_1 + S5.18hs_T_1 + S6.18hs_T_1 + S7.18hs_T_1 + S8.18hs_T_1 + S9.18hs_T_1 + Est.humedad_med_T_1 + Est.humedad_max_T_1
## Coefficients:
## (Intercept) S11.max_T_2 S13.max_T_2
## -5.899488e+00 1.609729e+00 -9.798895e-01
## S14.max_T_2 S15.max_T_2 S16.max_T_2
## 2.223232e+00 -7.042629e-01 6.267880e-01
## S1.max_T_2 S20.max_T_2 S2.max_T_2
## 1.000549e-02 4.838020e-01 -2.180788e+00
## S3.max_T_2 S5.max_T_2 S6.max_T_2
## 2.817616e-01 -1.959845e+00 -4.362590e-01
## S7.max_T_2 S8.max_T_2 S9.max_T_2
## 7.636357e-01 2.235428e-01 8.326056e-02
## S10.media_T_2 S11.media_T_2 S13.media_T_2
## -3.495246e+00 7.312998e-02 -2.301037e+00
## S14.media_T_2 S15.media_T_2 S16.media_T_2
## -2.740044e+00 -2.934794e+00 3.053468e+00
## S17.media_T_2 S19.media_T_2 S20.media_T_2
## 8.101288e-01 -4.010911e+00 -1.301619e+00
## S2.media_T_2 S3.media_T_2 S4.media_T_2
## 5.420250e-01 1.271415e+00 1.532663e+00
## S5.media_T_2 S6.media_T_2 S7.media_T_2
## -6.740137e+00 -1.916575e+00 1.069929e+01
## S8.media_T_2 S9.media_T_2 S12.min_T_2
## 3.211753e+00 3.897724e+00 2.292271e-01
## S14.min_T_2 S16.min_T_2 S18.min_T_2
## -1.673962e-01 1.338720e+00 9.691806e-02
## S19.min_T_2 S1.min_T_2 S20.min_T_2
## -1.236143e+00 3.968511e-01 -1.330587e+00
## S2.min_T_2 S3.min_T_2 S4.min_T_2
## -3.862183e-01 -4.547137e-01 4.168046e+00
## S5.min_T_2 S6.min_T_2 S8.min_T_2
## 6.727752e-01 1.783600e+00 -1.885829e+00
## S9.min_T_2 S10.15hs_T_2 S11.15hs_T_2
## -2.876709e+00 -2.041998e-01 3.151387e-01
## S12.15hs_T_2 S13.15hs_T_2 S14.15hs_T_2
## -3.467190e+00 4.820284e+00 -3.465732e+00
## S17.15hs_T_2 S18.15hs_T_2 S19.15hs_T_2
## -2.331526e+00 3.494137e+00 4.233272e-02
## S20.15hs_T_2 S2.15hs_T_2 S4.15hs_T_2
## 1.059354e-04 2.821655e+00 7.920470e-01
## S5.15hs_T_2 S6.15hs_T_2 S7.15hs_T_2
## 5.653660e-03 8.846673e-01 -1.513216e-01
## S8.15hs_T_2 S9.15hs_T_2 S10.12hs_T_2
## -2.961881e+00 -1.177791e-01 -1.847576e+00
## S12.12hs_T_2 S13.12hs_T_2 S14.12hs_T_2
## -1.455191e+00 -3.158866e+00 -2.740434e-01
## S15.12hs_T_2 S17.12hs_T_2 S18.12hs_T_2
## 3.722258e+00 2.334491e-01 -7.638806e-01
## S20.12hs_T_2 S3.12hs_T_2 S5.12hs_T_2
## -5.087867e-03 -3.110735e-01 2.756797e+00
## S6.12hs_T_2 S7.12hs_T_2 S8.12hs_T_2
## -5.298543e-01 -1.264709e+00 1.576397e+00
## S9.12hs_T_2 S10.18hs_T_2 S11.18hs_T_2
## 7.370516e-01 -1.590006e+00 -4.168134e+00
## S12.18hs_T_2 S14.18hs_T_2 S15.18hs_T_2
## 2.145002e+00 2.091566e+00 4.089653e+00
## S16.18hs_T_2 S18.18hs_T_2 S1.18hs_T_2
## -1.687392e+00 -2.634843e+00 -2.131819e+00
## S20.18hs_T_2 S2.18hs_T_2 S3.18hs_T_2
## 1.026327e+00 2.645759e+00 -1.865027e+00
## S4.18hs_T_2 S5.18hs_T_2 S6.18hs_T_2
## -2.044329e+00 -5.319535e-01 3.545236e+00
## S7.18hs_T_2 S8.18hs_T_2 S9.18hs_T_2
## -3.848331e-02 3.750887e-01 6.038710e-01
## Est.temp_max_T_2 S12.max_T_1 S14.max_T_1
## 2.685658e-01 -1.143630e+00 6.902709e-01
## S15.max_T_1 S17.max_T_1 S18.max_T_1
## -2.022569e+00 -7.918426e-01 1.289433e+00
## S1.max_T_1 S2.max_T_1 S3.max_T_1
## -2.073991e+00 7.479526e-01 -1.731269e+00
## S4.max_T_1 S6.max_T_1 S7.max_T_1
## 1.589548e+00 -1.724157e+00 9.170479e-01
## S8.max_T_1 S9.max_T_1 S10.media_T_1
## 3.511943e+00 3.507197e-01 8.986324e+00
## S11.media_T_1 S13.media_T_1 S14.media_T_1
## 2.717967e+00 -3.104687e-01 -7.373177e-03
## S15.media_T_1 S16.media_T_1 S17.media_T_1
## -1.297410e-01 -2.209819e+00 3.663587e+00
## S19.media_T_1 S20.media_T_1 S3.media_T_1
## 1.893530e-02 -6.515595e+00 3.701314e+00
## S4.media_T_1 S5.media_T_1 S6.media_T_1
## -1.100366e+00 -1.017200e+01 8.489418e+00
## S7.media_T_1 S8.media_T_1 S9.media_T_1
## -1.276452e+01 1.013972e+01 -3.034528e+00
## S10.min_T_1 S11.min_T_1 S12.min_T_1
## -5.209775e-01 3.573456e-01 4.637091e+00
## S13.min_T_1 S14.min_T_1 S15.min_T_1
## 5.717247e-01 -2.378973e+00 -9.378207e-02
## S16.min_T_1 S17.min_T_1 S18.min_T_1
## -3.525162e+00 1.024509e+00 1.375091e+00
## S19.min_T_1 S1.min_T_1 S3.min_T_1
## -2.063241e+00 9.836706e-01 -1.854240e-02
## S8.min_T_1 S10.15hs_T_1 S11.15hs_T_1
## -3.058271e-01 -5.710242e+00 1.337601e-01
## S12.15hs_T_1 S13.15hs_T_1 S14.15hs_T_1
## 1.838174e+00 -1.668685e+00 -4.544227e-01
## S15.15hs_T_1 S1.15hs_T_1 S20.15hs_T_1
## 5.699164e-01 8.341328e-01 1.240834e+00
## S2.15hs_T_1 S3.15hs_T_1 S7.15hs_T_1
## -7.349919e-01 1.635526e+00 2.172570e+00
## S8.15hs_T_1 S9.15hs_T_1 S10.12hs_T_1
## 8.840837e-01 -2.067009e-01 1.070872e+00
## S11.12hs_T_1 S12.12hs_T_1 S14.12hs_T_1
## -1.652270e+00 -1.601414e+00 2.741574e-01
## S15.12hs_T_1 S16.12hs_T_1 S19.12hs_T_1
## 1.058090e-02 -5.091448e-01 2.229486e+00
## S20.12hs_T_1 S3.12hs_T_1 S4.12hs_T_1
## 8.768571e-01 3.512549e-01 -5.367474e-01
## S5.12hs_T_1 S6.12hs_T_1 S7.12hs_T_1
## 2.416697e+00 -1.068102e+00 1.988868e+00
## S8.12hs_T_1 S10.18hs_T_1 S12.18hs_T_1
## -3.914418e+00 -7.062248e-01 4.108259e+00
## S16.18hs_T_1 S17.18hs_T_1 S19.18hs_T_1
## 2.039671e+00 -3.135132e+00 -3.130198e-01
## S20.18hs_T_1 S2.18hs_T_1 S5.18hs_T_1
## 8.650625e-01 -1.076170e-01 -9.278231e-01
## S6.18hs_T_1 S7.18hs_T_1 S8.18hs_T_1
## 9.236875e-01 -4.857458e-01 -2.415164e+00
## S9.18hs_T_1 Est.humedad_med_T_1 Est.humedad_max_T_1
## -3.868341e-01 3.546928e-01 -3.384848e-01
## Standard deviation of the residuals: 1.921144e-07
##
## $S9.min_t
##
## Parameters of node S9.min_t (Gaussian distribution)
##
## Conditional density: S9.min_t | S10.max_T_2 + S11.max_T_2 + S13.max_T_2 + S14.max_T_2 + S15.max_T_2 + S17.max_T_2 + S19.max_T_2 + S20.max_T_2 + S2.max_T_2 + S5.max_T_2 + S6.max_T_2 + S8.max_T_2 + S9.max_T_2 + S10.media_T_2 + S11.media_T_2 + S12.media_T_2 + S13.media_T_2 + S17.media_T_2 + S18.media_T_2 + S19.media_T_2 + S4.media_T_2 + S6.media_T_2 + S7.media_T_2 + S8.media_T_2 + S9.media_T_2 + S10.min_T_2 + S11.min_T_2 + S12.min_T_2 + S14.min_T_2 + S15.min_T_2 + S16.min_T_2 + S17.min_T_2 + S18.min_T_2 + S19.min_T_2 + S1.min_T_2 + S20.min_T_2 + S3.min_T_2 + S5.min_T_2 + S6.min_T_2 + S7.min_T_2 + S9.min_T_2 + S10.15hs_T_2 + S11.15hs_T_2 + S12.15hs_T_2 + S13.15hs_T_2 + S16.15hs_T_2 + S17.15hs_T_2 + S18.15hs_T_2 + S1.15hs_T_2 + S20.15hs_T_2 + S2.15hs_T_2 + S4.15hs_T_2 + S6.15hs_T_2 + S9.15hs_T_2 + S11.12hs_T_2 + S12.12hs_T_2 + S16.12hs_T_2 + S17.12hs_T_2 + S18.12hs_T_2 + S19.12hs_T_2 + S1.12hs_T_2 + S20.12hs_T_2 + S2.12hs_T_2 + S3.12hs_T_2 + S4.12hs_T_2 + S5.12hs_T_2 + S7.12hs_T_2 + S9.12hs_T_2 + S10.18hs_T_2 + S12.18hs_T_2 + S13.18hs_T_2 + S14.18hs_T_2 + S15.18hs_T_2 + S17.18hs_T_2 + S18.18hs_T_2 + S19.18hs_T_2 + S1.18hs_T_2 + S20.18hs_T_2 + S3.18hs_T_2 + S5.18hs_T_2 + S6.18hs_T_2 + S7.18hs_T_2 + S9.18hs_T_2 + Est.humedad_min_T_2 + Est.temp_min_T_2 + Est.temp_max_T_2 + S11.max_T_1 + S12.max_T_1 + S13.max_T_1 + S14.max_T_1 + S16.max_T_1 + S17.max_T_1 + S19.max_T_1 + S1.max_T_1 + S20.max_T_1 + S2.max_T_1 + S4.max_T_1 + S5.max_T_1 + S6.max_T_1 + S7.max_T_1 + S8.max_T_1 + S9.max_T_1 + S10.media_T_1 + S11.media_T_1 + S12.media_T_1 + S13.media_T_1 + S14.media_T_1 + S16.media_T_1 + S17.media_T_1 + S19.media_T_1 + S1.media_T_1 + S20.media_T_1 + S2.media_T_1 + S3.media_T_1 + S4.media_T_1 + S5.media_T_1 + S6.media_T_1 + S7.media_T_1 + S8.media_T_1 + S9.media_T_1 + S10.min_T_1 + S11.min_T_1 + S12.min_T_1 + S13.min_T_1 + S14.min_T_1 + S16.min_T_1 + S19.min_T_1 + S20.min_T_1 + S2.min_T_1 + S4.min_T_1 + S5.min_T_1 + S6.min_T_1 + S8.min_T_1 + S9.min_T_1 + S10.15hs_T_1 + S11.15hs_T_1 + S12.15hs_T_1 + S13.15hs_T_1 + S16.15hs_T_1 + S20.15hs_T_1 + S3.15hs_T_1 + S4.15hs_T_1 + S5.15hs_T_1 + S8.15hs_T_1 + S9.15hs_T_1 + S11.12hs_T_1 + S13.12hs_T_1 + S14.12hs_T_1 + S15.12hs_T_1 + S16.12hs_T_1 + S17.12hs_T_1 + S18.12hs_T_1 + S19.12hs_T_1 + S1.12hs_T_1 + S20.12hs_T_1 + S2.12hs_T_1 + S3.12hs_T_1 + S6.12hs_T_1 + S7.12hs_T_1 + S8.12hs_T_1 + S9.12hs_T_1 + S10.18hs_T_1 + S13.18hs_T_1 + S17.18hs_T_1 + S20.18hs_T_1 + S2.18hs_T_1 + S3.18hs_T_1 + S4.18hs_T_1 + S5.18hs_T_1 + S6.18hs_T_1 + S7.18hs_T_1 + S8.18hs_T_1 + S9.18hs_T_1 + Est.humedad_min_T_1 + Est.humedad_med_T_1 + Est.temp_max_T_1
## Coefficients:
## (Intercept) S10.max_T_2 S11.max_T_2
## -0.3114892982 -1.1093485456 0.1217796584
## S13.max_T_2 S14.max_T_2 S15.max_T_2
## 1.0660260586 -0.3900137895 -1.7671445237
## S17.max_T_2 S19.max_T_2 S20.max_T_2
## 0.8443828191 -0.1634561851 1.4498200998
## S2.max_T_2 S5.max_T_2 S6.max_T_2
## -2.8265471262 -1.5866840214 1.7553756429
## S8.max_T_2 S9.max_T_2 S10.media_T_2
## 0.9389726007 2.4362728678 -1.5333359559
## S11.media_T_2 S12.media_T_2 S13.media_T_2
## -3.3029847145 5.4708865014 -0.0166581082
## S17.media_T_2 S18.media_T_2 S19.media_T_2
## -5.0771082379 -4.0793640322 -5.2315564686
## S4.media_T_2 S6.media_T_2 S7.media_T_2
## 9.4701864055 -9.8491753939 19.2402139135
## S8.media_T_2 S9.media_T_2 S10.min_T_2
## -1.1706866635 -4.0826385223 3.5067666630
## S11.min_T_2 S12.min_T_2 S14.min_T_2
## 0.9658705229 1.9328519194 -0.6970565243
## S15.min_T_2 S16.min_T_2 S17.min_T_2
## 0.0004740995 -1.6512863333 2.7702324156
## S18.min_T_2 S19.min_T_2 S1.min_T_2
## 0.0149255426 -0.9844700953 -1.1575412096
## S20.min_T_2 S3.min_T_2 S5.min_T_2
## 4.4253121103 -0.3072736558 -0.4879100097
## S6.min_T_2 S7.min_T_2 S9.min_T_2
## -2.3687287213 -0.4913781573 -5.1900908325
## S10.15hs_T_2 S11.15hs_T_2 S12.15hs_T_2
## -0.8127900692 0.1276898365 -1.7788598068
## S13.15hs_T_2 S16.15hs_T_2 S17.15hs_T_2
## 1.7672720671 0.6737434729 -1.1821650657
## S18.15hs_T_2 S1.15hs_T_2 S20.15hs_T_2
## 4.0545514310 -1.9952996912 1.1435771264
## S2.15hs_T_2 S4.15hs_T_2 S6.15hs_T_2
## 0.0085472676 -0.7198818057 0.9543621610
## S9.15hs_T_2 S11.12hs_T_2 S12.12hs_T_2
## -2.4506082267 -0.1705503764 -2.9902113078
## S16.12hs_T_2 S17.12hs_T_2 S18.12hs_T_2
## -1.6361379629 0.9045618955 0.6097771632
## S19.12hs_T_2 S1.12hs_T_2 S20.12hs_T_2
## 0.0126406826 -0.3710371729 0.0472877404
## S2.12hs_T_2 S3.12hs_T_2 S4.12hs_T_2
## 0.3140169709 -0.2679450442 -0.3477276583
## S5.12hs_T_2 S7.12hs_T_2 S9.12hs_T_2
## 2.4799412883 -1.2001699609 2.5085882660
## S10.18hs_T_2 S12.18hs_T_2 S13.18hs_T_2
## -3.5842503318 2.0767112988 -3.0812796049
## S14.18hs_T_2 S15.18hs_T_2 S17.18hs_T_2
## 2.2630754955 1.2994367579 1.5768462369
## S18.18hs_T_2 S19.18hs_T_2 S1.18hs_T_2
## 0.0432250285 1.7991301517 -0.4068488446
## S20.18hs_T_2 S3.18hs_T_2 S5.18hs_T_2
## -0.0237568600 -2.4113676397 0.3067195494
## S6.18hs_T_2 S7.18hs_T_2 S9.18hs_T_2
## 0.0465586693 -0.4782775040 -0.1173245003
## Est.humedad_min_T_2 Est.temp_min_T_2 Est.temp_max_T_2
## -0.0682251083 0.2468680203 -0.2326889338
## S11.max_T_1 S12.max_T_1 S13.max_T_1
## 3.1829656992 -1.1963961829 0.1984392454
## S14.max_T_1 S16.max_T_1 S17.max_T_1
## 0.0175047985 0.7637004823 -0.6481560666
## S19.max_T_1 S1.max_T_1 S20.max_T_1
## -0.7620218519 -1.4625115885 -0.9116999626
## S2.max_T_1 S4.max_T_1 S5.max_T_1
## 2.3652601714 1.6323717175 -0.5878914614
## S6.max_T_1 S7.max_T_1 S8.max_T_1
## -0.2425793984 -1.5684170635 0.2507855644
## S9.max_T_1 S10.media_T_1 S11.media_T_1
## -0.3805203496 9.0287700715 -4.0417621469
## S12.media_T_1 S13.media_T_1 S14.media_T_1
## 0.0026861529 1.1225121838 -6.2516548695
## S16.media_T_1 S17.media_T_1 S19.media_T_1
## 4.3620784250 0.1845211462 2.6211377555
## S1.media_T_1 S20.media_T_1 S2.media_T_1
## 3.8034778660 -6.6827531434 -1.8597258449
## S3.media_T_1 S4.media_T_1 S5.media_T_1
## 8.3289587070 2.3571471603 -9.2185612863
## S6.media_T_1 S7.media_T_1 S8.media_T_1
## 3.2496783402 -8.6085117758 13.0386266364
## S9.media_T_1 S10.min_T_1 S11.min_T_1
## -9.6408816705 1.1804234371 0.5970091343
## S12.min_T_1 S13.min_T_1 S14.min_T_1
## 4.0930761580 -0.9561010054 0.5416723866
## S16.min_T_1 S19.min_T_1 S20.min_T_1
## -2.8038748331 0.6426297206 1.0902119525
## S2.min_T_1 S4.min_T_1 S5.min_T_1
## 0.1276747809 -0.6591963542 0.2636398478
## S6.min_T_1 S8.min_T_1 S9.min_T_1
## -1.5326840237 -1.6371884339 -1.0164709614
## S10.15hs_T_1 S11.15hs_T_1 S12.15hs_T_1
## -0.1501930977 -2.6787067057 -0.0376251415
## S13.15hs_T_1 S16.15hs_T_1 S20.15hs_T_1
## 1.0343658777 0.3157955029 2.7096208832
## S3.15hs_T_1 S4.15hs_T_1 S5.15hs_T_1
## 0.9689433207 -3.1094011234 2.4717485395
## S8.15hs_T_1 S9.15hs_T_1 S11.12hs_T_1
## -1.7823373661 0.5723874931 0.7140026659
## S13.12hs_T_1 S14.12hs_T_1 S15.12hs_T_1
## -2.1218873832 1.6996311685 -0.7753029606
## S16.12hs_T_1 S17.12hs_T_1 S18.12hs_T_1
## 0.0278554422 -0.5010153771 -0.5138605561
## S19.12hs_T_1 S1.12hs_T_1 S20.12hs_T_1
## 1.6824511370 -1.4453994283 -1.3612808541
## S2.12hs_T_1 S3.12hs_T_1 S6.12hs_T_1
## 0.3295802078 0.0215274467 -2.9760332262
## S7.12hs_T_1 S8.12hs_T_1 S9.12hs_T_1
## 4.1065510416 -1.7513856293 2.3093691644
## S10.18hs_T_1 S13.18hs_T_1 S17.18hs_T_1
## -0.8348528978 0.8472077353 -0.1004667619
## S20.18hs_T_1 S2.18hs_T_1 S3.18hs_T_1
## 0.7629241239 -0.1435606249 -0.9320452721
## S4.18hs_T_1 S5.18hs_T_1 S6.18hs_T_1
## 0.8295461286 -2.8224492491 2.6980456729
## S7.18hs_T_1 S8.18hs_T_1 S9.18hs_T_1
## -2.2733567271 -0.4576760473 1.3888234796
## Est.humedad_min_T_1 Est.humedad_med_T_1 Est.temp_max_T_1
## -0.1133718588 0.1127897265 -0.0568663212
## Standard deviation of the residuals: 3.618578e-07bn.fit.qqplot(fitted[[ncol(df)]])
bn.fit.xyplot(fitted[[ncol(df)]])
bn.fit.histogram(fitted[[ncol(df)]])
Markov blanket de las variables de interés para predecir
for(i in 1:length(pred_sensores))
{
cat("Markov blanket of ",pred_sensores[i],"\n")
print(mb(res,pred_sensores[i]))
}## Markov blanket of S10.min_t
## [1] "S10.max_T_2" "S11.max_T_2" "S12.max_T_2"
## [4] "S14.max_T_2" "S15.max_T_2" "S16.max_T_2"
## [7] "S17.max_T_2" "S18.max_T_2" "S1.max_T_2"
## [10] "S20.max_T_2" "S2.max_T_2" "S3.max_T_2"
## [13] "S5.max_T_2" "S6.max_T_2" "S8.max_T_2"
## [16] "S10.media_T_2" "S11.media_T_2" "S12.media_T_2"
## [19] "S13.media_T_2" "S15.media_T_2" "S17.media_T_2"
## [22] "S18.media_T_2" "S20.media_T_2" "S2.media_T_2"
## [25] "S3.media_T_2" "S4.media_T_2" "S6.media_T_2"
## [28] "S7.media_T_2" "S8.media_T_2" "S9.media_T_2"
## [31] "S10.min_T_2" "S12.min_T_2" "S15.min_T_2"
## [34] "S16.min_T_2" "S17.min_T_2" "S18.min_T_2"
## [37] "S1.min_T_2" "S20.min_T_2" "S2.min_T_2"
## [40] "S3.min_T_2" "S4.min_T_2" "S5.min_T_2"
## [43] "S7.min_T_2" "S8.min_T_2" "S9.min_T_2"
## [46] "S10.15hs_T_2" "S11.15hs_T_2" "S12.15hs_T_2"
## [49] "S13.15hs_T_2" "S14.15hs_T_2" "S16.15hs_T_2"
## [52] "S17.15hs_T_2" "S18.15hs_T_2" "S19.15hs_T_2"
## [55] "S1.15hs_T_2" "S2.15hs_T_2" "S3.15hs_T_2"
## [58] "S4.15hs_T_2" "S5.15hs_T_2" "S6.15hs_T_2"
## [61] "S8.15hs_T_2" "S9.15hs_T_2" "S10.12hs_T_2"
## [64] "S11.12hs_T_2" "S12.12hs_T_2" "S14.12hs_T_2"
## [67] "S15.12hs_T_2" "S16.12hs_T_2" "S17.12hs_T_2"
## [70] "S18.12hs_T_2" "S19.12hs_T_2" "S1.12hs_T_2"
## [73] "S20.12hs_T_2" "S2.12hs_T_2" "S3.12hs_T_2"
## [76] "S5.12hs_T_2" "S7.12hs_T_2" "S8.12hs_T_2"
## [79] "S9.12hs_T_2" "S10.18hs_T_2" "S11.18hs_T_2"
## [82] "S12.18hs_T_2" "S14.18hs_T_2" "S15.18hs_T_2"
## [85] "S16.18hs_T_2" "S17.18hs_T_2" "S18.18hs_T_2"
## [88] "S1.18hs_T_2" "S20.18hs_T_2" "S2.18hs_T_2"
## [91] "S3.18hs_T_2" "S4.18hs_T_2" "S6.18hs_T_2"
## [94] "S7.18hs_T_2" "S8.18hs_T_2" "S9.18hs_T_2"
## [97] "Est.humedad_min_T_2" "Est.humedad_med_T_2" "S10.max_T_1"
## [100] "S11.max_T_1" "S13.max_T_1" "S15.max_T_1"
## [103] "S18.max_T_1" "S19.max_T_1" "S20.max_T_1"
## [106] "S2.max_T_1" "S3.max_T_1" "S4.max_T_1"
## [109] "S6.max_T_1" "S7.max_T_1" "S8.max_T_1"
## [112] "S9.max_T_1" "S10.media_T_1" "S13.media_T_1"
## [115] "S15.media_T_1" "S16.media_T_1" "S18.media_T_1"
## [118] "S20.media_T_1" "S2.media_T_1" "S3.media_T_1"
## [121] "S4.media_T_1" "S5.media_T_1" "S6.media_T_1"
## [124] "S7.media_T_1" "S8.media_T_1" "S10.min_T_1"
## [127] "S11.min_T_1" "S12.min_T_1" "S13.min_T_1"
## [130] "S14.min_T_1" "S16.min_T_1" "S18.min_T_1"
## [133] "S19.min_T_1" "S20.min_T_1" "S2.min_T_1"
## [136] "S3.min_T_1" "S4.min_T_1" "S5.min_T_1"
## [139] "S6.min_T_1" "S7.min_T_1" "S8.min_T_1"
## [142] "S9.min_T_1" "S10.15hs_T_1" "S12.15hs_T_1"
## [145] "S13.15hs_T_1" "S14.15hs_T_1" "S16.15hs_T_1"
## [148] "S17.15hs_T_1" "S19.15hs_T_1" "S1.15hs_T_1"
## [151] "S20.15hs_T_1" "S3.15hs_T_1" "S4.15hs_T_1"
## [154] "S8.15hs_T_1" "S9.15hs_T_1" "S10.12hs_T_1"
## [157] "S13.12hs_T_1" "S14.12hs_T_1" "S15.12hs_T_1"
## [160] "S16.12hs_T_1" "S17.12hs_T_1" "S19.12hs_T_1"
## [163] "S1.12hs_T_1" "S20.12hs_T_1" "S2.12hs_T_1"
## [166] "S3.12hs_T_1" "S4.12hs_T_1" "S5.12hs_T_1"
## [169] "S6.12hs_T_1" "S7.12hs_T_1" "S8.12hs_T_1"
## [172] "S9.12hs_T_1" "S10.18hs_T_1" "S11.18hs_T_1"
## [175] "S12.18hs_T_1" "S13.18hs_T_1" "S14.18hs_T_1"
## [178] "S15.18hs_T_1" "S16.18hs_T_1" "S17.18hs_T_1"
## [181] "S18.18hs_T_1" "S19.18hs_T_1" "S1.18hs_T_1"
## [184] "S20.18hs_T_1" "S2.18hs_T_1" "S3.18hs_T_1"
## [187] "S4.18hs_T_1" "S5.18hs_T_1" "S6.18hs_T_1"
## [190] "S7.18hs_T_1" "S9.18hs_T_1" "Est.humedad_min_T_1"
## [193] "Est.temp_min_T_1" "Est.temp_max_T_1" "Est.temp_med_T_1"
## [196] "S11.min_t" "S20.min_t" "S6.min_t"
## Markov blanket of S11.min_t
## [1] "S10.max_T_2" "S11.max_T_2" "S12.max_T_2"
## [4] "S13.max_T_2" "S14.max_T_2" "S16.max_T_2"
## [7] "S17.max_T_2" "S18.max_T_2" "S19.max_T_2"
## [10] "S1.max_T_2" "S20.max_T_2" "S2.max_T_2"
## [13] "S5.max_T_2" "S6.max_T_2" "S7.max_T_2"
## [16] "S9.max_T_2" "S10.media_T_2" "S11.media_T_2"
## [19] "S12.media_T_2" "S14.media_T_2" "S17.media_T_2"
## [22] "S18.media_T_2" "S19.media_T_2" "S3.media_T_2"
## [25] "S4.media_T_2" "S5.media_T_2" "S6.media_T_2"
## [28] "S7.media_T_2" "S10.min_T_2" "S11.min_T_2"
## [31] "S12.min_T_2" "S13.min_T_2" "S14.min_T_2"
## [34] "S15.min_T_2" "S16.min_T_2" "S17.min_T_2"
## [37] "S18.min_T_2" "S1.min_T_2" "S20.min_T_2"
## [40] "S2.min_T_2" "S4.min_T_2" "S6.min_T_2"
## [43] "S7.min_T_2" "S9.min_T_2" "S10.15hs_T_2"
## [46] "S11.15hs_T_2" "S12.15hs_T_2" "S13.15hs_T_2"
## [49] "S16.15hs_T_2" "S17.15hs_T_2" "S18.15hs_T_2"
## [52] "S19.15hs_T_2" "S1.15hs_T_2" "S2.15hs_T_2"
## [55] "S3.15hs_T_2" "S4.15hs_T_2" "S5.15hs_T_2"
## [58] "S7.15hs_T_2" "S9.15hs_T_2" "S11.12hs_T_2"
## [61] "S12.12hs_T_2" "S14.12hs_T_2" "S18.12hs_T_2"
## [64] "S19.12hs_T_2" "S1.12hs_T_2" "S2.12hs_T_2"
## [67] "S3.12hs_T_2" "S7.12hs_T_2" "S8.12hs_T_2"
## [70] "S9.12hs_T_2" "S10.18hs_T_2" "S11.18hs_T_2"
## [73] "S12.18hs_T_2" "S13.18hs_T_2" "S14.18hs_T_2"
## [76] "S15.18hs_T_2" "S16.18hs_T_2" "S17.18hs_T_2"
## [79] "S18.18hs_T_2" "S19.18hs_T_2" "S1.18hs_T_2"
## [82] "S20.18hs_T_2" "S4.18hs_T_2" "S5.18hs_T_2"
## [85] "S8.18hs_T_2" "S9.18hs_T_2" "Est.humedad_min_T_2"
## [88] "S10.max_T_1" "S11.max_T_1" "S12.max_T_1"
## [91] "S13.max_T_1" "S14.max_T_1" "S15.max_T_1"
## [94] "S17.max_T_1" "S18.max_T_1" "S19.max_T_1"
## [97] "S1.max_T_1" "S20.max_T_1" "S2.max_T_1"
## [100] "S3.max_T_1" "S4.max_T_1" "S5.max_T_1"
## [103] "S6.max_T_1" "S7.max_T_1" "S8.max_T_1"
## [106] "S9.max_T_1" "S10.media_T_1" "S11.media_T_1"
## [109] "S12.media_T_1" "S14.media_T_1" "S16.media_T_1"
## [112] "S17.media_T_1" "S18.media_T_1" "S1.media_T_1"
## [115] "S20.media_T_1" "S2.media_T_1" "S3.media_T_1"
## [118] "S4.media_T_1" "S5.media_T_1" "S6.media_T_1"
## [121] "S7.media_T_1" "S8.media_T_1" "S9.media_T_1"
## [124] "S10.min_T_1" "S11.min_T_1" "S12.min_T_1"
## [127] "S13.min_T_1" "S15.min_T_1" "S16.min_T_1"
## [130] "S18.min_T_1" "S19.min_T_1" "S1.min_T_1"
## [133] "S20.min_T_1" "S2.min_T_1" "S3.min_T_1"
## [136] "S4.min_T_1" "S6.min_T_1" "S7.min_T_1"
## [139] "S8.min_T_1" "S10.15hs_T_1" "S11.15hs_T_1"
## [142] "S12.15hs_T_1" "S13.15hs_T_1" "S14.15hs_T_1"
## [145] "S16.15hs_T_1" "S18.15hs_T_1" "S19.15hs_T_1"
## [148] "S1.15hs_T_1" "S2.15hs_T_1" "S4.15hs_T_1"
## [151] "S6.15hs_T_1" "S9.15hs_T_1" "S11.12hs_T_1"
## [154] "S12.12hs_T_1" "S14.12hs_T_1" "S16.12hs_T_1"
## [157] "S17.12hs_T_1" "S18.12hs_T_1" "S1.12hs_T_1"
## [160] "S20.12hs_T_1" "S2.12hs_T_1" "S3.12hs_T_1"
## [163] "S4.12hs_T_1" "S5.12hs_T_1" "S6.12hs_T_1"
## [166] "S7.12hs_T_1" "S8.12hs_T_1" "S10.18hs_T_1"
## [169] "S11.18hs_T_1" "S12.18hs_T_1" "S13.18hs_T_1"
## [172] "S14.18hs_T_1" "S16.18hs_T_1" "S17.18hs_T_1"
## [175] "S18.18hs_T_1" "S19.18hs_T_1" "S1.18hs_T_1"
## [178] "S20.18hs_T_1" "S2.18hs_T_1" "S4.18hs_T_1"
## [181] "S6.18hs_T_1" "S7.18hs_T_1" "S8.18hs_T_1"
## [184] "S9.18hs_T_1" "Est.humedad_min_T_1" "Est.humedad_med_T_1"
## [187] "Est.humedad_max_T_1" "Est.temp_min_T_1" "Est.temp_max_T_1"
## [190] "Est.temp_med_T_1" "S10.min_t" "S6.min_t"
## Markov blanket of S12.min_t
## [1] "S11.max_T_2" "S12.max_T_2" "S16.max_T_2"
## [4] "S19.max_T_2" "S8.max_T_2" "S12.media_T_2"
## [7] "S15.media_T_2" "S20.media_T_2" "S3.media_T_2"
## [10] "S4.media_T_2" "S6.media_T_2" "S10.min_T_2"
## [13] "S12.min_T_2" "S16.min_T_2" "S9.min_T_2"
## [16] "S12.15hs_T_2" "S13.15hs_T_2" "S17.15hs_T_2"
## [19] "S5.15hs_T_2" "S6.15hs_T_2" "S12.12hs_T_2"
## [22] "S5.12hs_T_2" "S9.12hs_T_2" "S10.18hs_T_2"
## [25] "S12.18hs_T_2" "S14.18hs_T_2" "S17.18hs_T_2"
## [28] "S1.18hs_T_2" "S4.18hs_T_2" "S7.18hs_T_2"
## [31] "Est.temp_min_T_2" "S12.max_T_1" "S14.max_T_1"
## [34] "S17.max_T_1" "S1.max_T_1" "S2.max_T_1"
## [37] "S3.max_T_1" "S9.max_T_1" "S12.media_T_1"
## [40] "S20.media_T_1" "S5.media_T_1" "S6.media_T_1"
## [43] "S8.media_T_1" "S12.min_T_1" "S14.min_T_1"
## [46] "S17.min_T_1" "S18.min_T_1" "S20.min_T_1"
## [49] "S6.min_T_1" "S8.min_T_1" "S12.15hs_T_1"
## [52] "S1.15hs_T_1" "S2.15hs_T_1" "S3.15hs_T_1"
## [55] "S12.12hs_T_1" "S16.12hs_T_1" "S18.12hs_T_1"
## [58] "S4.12hs_T_1" "S6.12hs_T_1" "S12.18hs_T_1"
## [61] "S3.18hs_T_1" "S4.18hs_T_1" "Est.humedad_min_T_1"
## Markov blanket of S13.min_t
## [1] "S10.max_T_2" "S11.max_T_2" "S12.max_T_2"
## [4] "S13.max_T_2" "S14.max_T_2" "S15.max_T_2"
## [7] "S17.max_T_2" "S18.max_T_2" "S20.max_T_2"
## [10] "S2.max_T_2" "S5.max_T_2" "S8.max_T_2"
## [13] "S9.max_T_2" "S10.media_T_2" "S11.media_T_2"
## [16] "S12.media_T_2" "S13.media_T_2" "S14.media_T_2"
## [19] "S15.media_T_2" "S17.media_T_2" "S18.media_T_2"
## [22] "S19.media_T_2" "S1.media_T_2" "S3.media_T_2"
## [25] "S6.media_T_2" "S7.media_T_2" "S9.media_T_2"
## [28] "S10.min_T_2" "S11.min_T_2" "S12.min_T_2"
## [31] "S13.min_T_2" "S14.min_T_2" "S15.min_T_2"
## [34] "S16.min_T_2" "S17.min_T_2" "S18.min_T_2"
## [37] "S19.min_T_2" "S20.min_T_2" "S4.min_T_2"
## [40] "S8.min_T_2" "S9.min_T_2" "S12.15hs_T_2"
## [43] "S13.15hs_T_2" "S14.15hs_T_2" "S16.15hs_T_2"
## [46] "S17.15hs_T_2" "S18.15hs_T_2" "S19.15hs_T_2"
## [49] "S20.15hs_T_2" "S2.15hs_T_2" "S4.15hs_T_2"
## [52] "S5.15hs_T_2" "S7.15hs_T_2" "S8.15hs_T_2"
## [55] "S9.15hs_T_2" "S11.12hs_T_2" "S12.12hs_T_2"
## [58] "S13.12hs_T_2" "S15.12hs_T_2" "S17.12hs_T_2"
## [61] "S18.12hs_T_2" "S19.12hs_T_2" "S3.12hs_T_2"
## [64] "S4.12hs_T_2" "S5.12hs_T_2" "S6.12hs_T_2"
## [67] "S7.12hs_T_2" "S8.12hs_T_2" "S9.12hs_T_2"
## [70] "S10.18hs_T_2" "S11.18hs_T_2" "S12.18hs_T_2"
## [73] "S13.18hs_T_2" "S14.18hs_T_2" "S15.18hs_T_2"
## [76] "S17.18hs_T_2" "S18.18hs_T_2" "S1.18hs_T_2"
## [79] "S20.18hs_T_2" "S2.18hs_T_2" "S3.18hs_T_2"
## [82] "S4.18hs_T_2" "S5.18hs_T_2" "S6.18hs_T_2"
## [85] "S9.18hs_T_2" "Est.humedad_min_T_2" "Est.humedad_max_T_2"
## [88] "S10.max_T_1" "S13.max_T_1" "S14.max_T_1"
## [91] "S15.max_T_1" "S17.max_T_1" "S19.max_T_1"
## [94] "S1.max_T_1" "S2.max_T_1" "S3.max_T_1"
## [97] "S4.max_T_1" "S5.max_T_1" "S6.max_T_1"
## [100] "S8.max_T_1" "S10.media_T_1" "S12.media_T_1"
## [103] "S13.media_T_1" "S16.media_T_1" "S17.media_T_1"
## [106] "S18.media_T_1" "S19.media_T_1" "S1.media_T_1"
## [109] "S20.media_T_1" "S2.media_T_1" "S3.media_T_1"
## [112] "S5.media_T_1" "S6.media_T_1" "S7.media_T_1"
## [115] "S8.media_T_1" "S9.media_T_1" "S11.min_T_1"
## [118] "S12.min_T_1" "S13.min_T_1" "S16.min_T_1"
## [121] "S17.min_T_1" "S18.min_T_1" "S19.min_T_1"
## [124] "S1.min_T_1" "S2.min_T_1" "S3.min_T_1"
## [127] "S4.min_T_1" "S6.min_T_1" "S7.min_T_1"
## [130] "S9.min_T_1" "S10.15hs_T_1" "S13.15hs_T_1"
## [133] "S14.15hs_T_1" "S16.15hs_T_1" "S17.15hs_T_1"
## [136] "S18.15hs_T_1" "S19.15hs_T_1" "S20.15hs_T_1"
## [139] "S2.15hs_T_1" "S3.15hs_T_1" "S5.15hs_T_1"
## [142] "S6.15hs_T_1" "S7.15hs_T_1" "S9.15hs_T_1"
## [145] "S10.12hs_T_1" "S11.12hs_T_1" "S12.12hs_T_1"
## [148] "S13.12hs_T_1" "S14.12hs_T_1" "S15.12hs_T_1"
## [151] "S16.12hs_T_1" "S17.12hs_T_1" "S1.12hs_T_1"
## [154] "S2.12hs_T_1" "S4.12hs_T_1" "S6.12hs_T_1"
## [157] "S7.12hs_T_1" "S8.12hs_T_1" "S9.12hs_T_1"
## [160] "S10.18hs_T_1" "S11.18hs_T_1" "S12.18hs_T_1"
## [163] "S13.18hs_T_1" "S14.18hs_T_1" "S15.18hs_T_1"
## [166] "S17.18hs_T_1" "S18.18hs_T_1" "S1.18hs_T_1"
## [169] "S2.18hs_T_1" "S3.18hs_T_1" "S4.18hs_T_1"
## [172] "S5.18hs_T_1" "S7.18hs_T_1" "S8.18hs_T_1"
## [175] "S9.18hs_T_1" "Est.humedad_min_T_1"
## Markov blanket of S14.min_t
## [1] "S10.max_T_2" "S11.max_T_2" "S14.max_T_2"
## [4] "S16.max_T_2" "S20.max_T_2" "S2.max_T_2"
## [7] "S5.max_T_2" "S9.max_T_2" "S12.media_T_2"
## [10] "S13.media_T_2" "S14.media_T_2" "S2.media_T_2"
## [13] "S4.media_T_2" "S6.media_T_2" "S9.media_T_2"
## [16] "S12.min_T_2" "S14.min_T_2" "S16.min_T_2"
## [19] "S20.min_T_2" "S2.min_T_2" "S9.min_T_2"
## [22] "S12.15hs_T_2" "S13.15hs_T_2" "S14.15hs_T_2"
## [25] "S17.15hs_T_2" "S19.15hs_T_2" "S20.15hs_T_2"
## [28] "S2.15hs_T_2" "S3.15hs_T_2" "S4.15hs_T_2"
## [31] "S5.15hs_T_2" "S6.15hs_T_2" "S9.15hs_T_2"
## [34] "S10.12hs_T_2" "S14.12hs_T_2" "S5.12hs_T_2"
## [37] "S8.12hs_T_2" "S10.18hs_T_2" "S14.18hs_T_2"
## [40] "S16.18hs_T_2" "S17.18hs_T_2" "S19.18hs_T_2"
## [43] "S20.18hs_T_2" "S3.18hs_T_2" "S5.18hs_T_2"
## [46] "S6.18hs_T_2" "S7.18hs_T_2" "S8.18hs_T_2"
## [49] "S9.18hs_T_2" "Est.humedad_max_T_2" "S11.max_T_1"
## [52] "S13.max_T_1" "S14.max_T_1" "S17.max_T_1"
## [55] "S18.max_T_1" "S20.max_T_1" "S2.max_T_1"
## [58] "S3.max_T_1" "S8.max_T_1" "S9.max_T_1"
## [61] "S10.media_T_1" "S14.media_T_1" "S17.media_T_1"
## [64] "S5.media_T_1" "S6.media_T_1" "S7.media_T_1"
## [67] "S8.media_T_1" "S9.media_T_1" "S10.min_T_1"
## [70] "S12.min_T_1" "S14.min_T_1" "S16.min_T_1"
## [73] "S17.min_T_1" "S18.min_T_1" "S6.min_T_1"
## [76] "S8.min_T_1" "S10.15hs_T_1" "S12.15hs_T_1"
## [79] "S14.15hs_T_1" "S15.15hs_T_1" "S16.15hs_T_1"
## [82] "S18.15hs_T_1" "S1.15hs_T_1" "S2.15hs_T_1"
## [85] "S3.15hs_T_1" "S9.15hs_T_1" "S10.12hs_T_1"
## [88] "S13.12hs_T_1" "S14.12hs_T_1" "S15.12hs_T_1"
## [91] "S18.12hs_T_1" "S1.12hs_T_1" "S20.12hs_T_1"
## [94] "S4.12hs_T_1" "S5.12hs_T_1" "S6.12hs_T_1"
## [97] "S7.12hs_T_1" "S8.12hs_T_1" "S9.12hs_T_1"
## [100] "S10.18hs_T_1" "S11.18hs_T_1" "S12.18hs_T_1"
## [103] "S13.18hs_T_1" "S14.18hs_T_1" "S15.18hs_T_1"
## [106] "S17.18hs_T_1" "S18.18hs_T_1" "S19.18hs_T_1"
## [109] "S1.18hs_T_1" "S20.18hs_T_1" "S3.18hs_T_1"
## [112] "S5.18hs_T_1" "S6.18hs_T_1" "S7.18hs_T_1"
## [115] "Est.humedad_med_T_1" "Est.temp_min_T_1" "Est.temp_max_T_1"
## [118] "Est.temp_med_T_1" "S5.min_t"
## Markov blanket of S15.min_t
## [1] "S10.max_T_2" "S11.max_T_2" "S12.max_T_2"
## [4] "S14.max_T_2" "S15.max_T_2" "S18.max_T_2"
## [7] "S1.max_T_2" "S20.max_T_2" "S2.max_T_2"
## [10] "S3.max_T_2" "S5.max_T_2" "S7.max_T_2"
## [13] "S8.max_T_2" "S9.max_T_2" "S10.media_T_2"
## [16] "S12.media_T_2" "S13.media_T_2" "S15.media_T_2"
## [19] "S16.media_T_2" "S17.media_T_2" "S18.media_T_2"
## [22] "S20.media_T_2" "S4.media_T_2" "S5.media_T_2"
## [25] "S6.media_T_2" "S9.media_T_2" "S10.min_T_2"
## [28] "S11.min_T_2" "S12.min_T_2" "S15.min_T_2"
## [31] "S17.min_T_2" "S18.min_T_2" "S1.min_T_2"
## [34] "S20.min_T_2" "S2.min_T_2" "S5.min_T_2"
## [37] "S6.min_T_2" "S8.min_T_2" "S9.min_T_2"
## [40] "S12.15hs_T_2" "S13.15hs_T_2" "S14.15hs_T_2"
## [43] "S15.15hs_T_2" "S16.15hs_T_2" "S17.15hs_T_2"
## [46] "S18.15hs_T_2" "S2.15hs_T_2" "S3.15hs_T_2"
## [49] "S4.15hs_T_2" "S5.15hs_T_2" "S6.15hs_T_2"
## [52] "S7.15hs_T_2" "S9.15hs_T_2" "S10.12hs_T_2"
## [55] "S11.12hs_T_2" "S12.12hs_T_2" "S14.12hs_T_2"
## [58] "S15.12hs_T_2" "S16.12hs_T_2" "S17.12hs_T_2"
## [61] "S18.12hs_T_2" "S1.12hs_T_2" "S20.12hs_T_2"
## [64] "S2.12hs_T_2" "S3.12hs_T_2" "S5.12hs_T_2"
## [67] "S7.12hs_T_2" "S8.12hs_T_2" "S10.18hs_T_2"
## [70] "S11.18hs_T_2" "S14.18hs_T_2" "S15.18hs_T_2"
## [73] "S16.18hs_T_2" "S18.18hs_T_2" "S1.18hs_T_2"
## [76] "S20.18hs_T_2" "S2.18hs_T_2" "S3.18hs_T_2"
## [79] "S4.18hs_T_2" "S5.18hs_T_2" "S6.18hs_T_2"
## [82] "S7.18hs_T_2" "S8.18hs_T_2" "S9.18hs_T_2"
## [85] "Est.humedad_med_T_2" "Est.temp_max_T_2" "S10.max_T_1"
## [88] "S11.max_T_1" "S14.max_T_1" "S15.max_T_1"
## [91] "S16.max_T_1" "S17.max_T_1" "S19.max_T_1"
## [94] "S1.max_T_1" "S20.max_T_1" "S2.max_T_1"
## [97] "S3.max_T_1" "S4.max_T_1" "S7.max_T_1"
## [100] "S8.max_T_1" "S9.max_T_1" "S10.media_T_1"
## [103] "S11.media_T_1" "S12.media_T_1" "S13.media_T_1"
## [106] "S14.media_T_1" "S15.media_T_1" "S16.media_T_1"
## [109] "S18.media_T_1" "S1.media_T_1" "S2.media_T_1"
## [112] "S5.media_T_1" "S6.media_T_1" "S7.media_T_1"
## [115] "S8.media_T_1" "S9.media_T_1" "S12.min_T_1"
## [118] "S13.min_T_1" "S14.min_T_1" "S15.min_T_1"
## [121] "S17.min_T_1" "S18.min_T_1" "S19.min_T_1"
## [124] "S1.min_T_1" "S2.min_T_1" "S3.min_T_1"
## [127] "S4.min_T_1" "S5.min_T_1" "S6.min_T_1"
## [130] "S8.min_T_1" "S10.15hs_T_1" "S11.15hs_T_1"
## [133] "S12.15hs_T_1" "S15.15hs_T_1" "S16.15hs_T_1"
## [136] "S18.15hs_T_1" "S19.15hs_T_1" "S1.15hs_T_1"
## [139] "S20.15hs_T_1" "S2.15hs_T_1" "S3.15hs_T_1"
## [142] "S4.15hs_T_1" "S5.15hs_T_1" "S6.15hs_T_1"
## [145] "S7.15hs_T_1" "S9.15hs_T_1" "S10.12hs_T_1"
## [148] "S11.12hs_T_1" "S12.12hs_T_1" "S15.12hs_T_1"
## [151] "S16.12hs_T_1" "S18.12hs_T_1" "S19.12hs_T_1"
## [154] "S1.12hs_T_1" "S20.12hs_T_1" "S2.12hs_T_1"
## [157] "S3.12hs_T_1" "S4.12hs_T_1" "S5.12hs_T_1"
## [160] "S6.12hs_T_1" "S7.12hs_T_1" "S8.12hs_T_1"
## [163] "S12.18hs_T_1" "S13.18hs_T_1" "S14.18hs_T_1"
## [166] "S15.18hs_T_1" "S1.18hs_T_1" "S3.18hs_T_1"
## [169] "S5.18hs_T_1" "S6.18hs_T_1" "S7.18hs_T_1"
## [172] "S8.18hs_T_1" "S9.18hs_T_1" "Est.humedad_min_T_1"
## [175] "Est.humedad_med_T_1" "Est.temp_min_T_1"
## Markov blanket of S16.min_t
## [1] "S11.max_T_2" "S12.max_T_2" "S13.max_T_2"
## [4] "S14.max_T_2" "S15.max_T_2" "S16.max_T_2"
## [7] "S17.max_T_2" "S20.max_T_2" "S2.max_T_2"
## [10] "S5.max_T_2" "S6.max_T_2" "S7.max_T_2"
## [13] "S9.max_T_2" "S10.media_T_2" "S15.media_T_2"
## [16] "S16.media_T_2" "S17.media_T_2" "S18.media_T_2"
## [19] "S1.media_T_2" "S2.media_T_2" "S3.media_T_2"
## [22] "S4.media_T_2" "S6.media_T_2" "S7.media_T_2"
## [25] "S11.min_T_2" "S12.min_T_2" "S16.min_T_2"
## [28] "S17.min_T_2" "S18.min_T_2" "S19.min_T_2"
## [31] "S1.min_T_2" "S2.min_T_2" "S3.min_T_2"
## [34] "S4.min_T_2" "S5.min_T_2" "S9.min_T_2"
## [37] "S11.15hs_T_2" "S12.15hs_T_2" "S13.15hs_T_2"
## [40] "S14.15hs_T_2" "S15.15hs_T_2" "S16.15hs_T_2"
## [43] "S17.15hs_T_2" "S19.15hs_T_2" "S1.15hs_T_2"
## [46] "S3.15hs_T_2" "S4.15hs_T_2" "S5.15hs_T_2"
## [49] "S6.15hs_T_2" "S7.15hs_T_2" "S9.15hs_T_2"
## [52] "S12.12hs_T_2" "S13.12hs_T_2" "S14.12hs_T_2"
## [55] "S16.12hs_T_2" "S17.12hs_T_2" "S18.12hs_T_2"
## [58] "S2.12hs_T_2" "S4.12hs_T_2" "S6.12hs_T_2"
## [61] "S7.12hs_T_2" "S8.12hs_T_2" "S10.18hs_T_2"
## [64] "S12.18hs_T_2" "S13.18hs_T_2" "S14.18hs_T_2"
## [67] "S15.18hs_T_2" "S16.18hs_T_2" "S17.18hs_T_2"
## [70] "S18.18hs_T_2" "S1.18hs_T_2" "S20.18hs_T_2"
## [73] "S2.18hs_T_2" "S3.18hs_T_2" "S4.18hs_T_2"
## [76] "S5.18hs_T_2" "S6.18hs_T_2" "S7.18hs_T_2"
## [79] "S9.18hs_T_2" "Est.humedad_min_T_2" "Est.temp_med_T_2"
## [82] "S10.max_T_1" "S11.max_T_1" "S12.max_T_1"
## [85] "S13.max_T_1" "S14.max_T_1" "S15.max_T_1"
## [88] "S16.max_T_1" "S17.max_T_1" "S18.max_T_1"
## [91] "S1.max_T_1" "S2.max_T_1" "S3.max_T_1"
## [94] "S4.max_T_1" "S5.max_T_1" "S6.max_T_1"
## [97] "S7.max_T_1" "S8.max_T_1" "S10.media_T_1"
## [100] "S14.media_T_1" "S16.media_T_1" "S17.media_T_1"
## [103] "S18.media_T_1" "S19.media_T_1" "S1.media_T_1"
## [106] "S20.media_T_1" "S2.media_T_1" "S3.media_T_1"
## [109] "S6.media_T_1" "S7.media_T_1" "S9.media_T_1"
## [112] "S10.min_T_1" "S12.min_T_1" "S13.min_T_1"
## [115] "S14.min_T_1" "S15.min_T_1" "S16.min_T_1"
## [118] "S17.min_T_1" "S18.min_T_1" "S19.min_T_1"
## [121] "S1.min_T_1" "S20.min_T_1" "S2.min_T_1"
## [124] "S3.min_T_1" "S6.min_T_1" "S8.min_T_1"
## [127] "S9.min_T_1" "S10.15hs_T_1" "S11.15hs_T_1"
## [130] "S13.15hs_T_1" "S14.15hs_T_1" "S15.15hs_T_1"
## [133] "S16.15hs_T_1" "S17.15hs_T_1" "S18.15hs_T_1"
## [136] "S1.15hs_T_1" "S20.15hs_T_1" "S3.15hs_T_1"
## [139] "S4.15hs_T_1" "S5.15hs_T_1" "S6.15hs_T_1"
## [142] "S8.15hs_T_1" "S9.15hs_T_1" "S11.12hs_T_1"
## [145] "S12.12hs_T_1" "S14.12hs_T_1" "S15.12hs_T_1"
## [148] "S16.12hs_T_1" "S17.12hs_T_1" "S18.12hs_T_1"
## [151] "S19.12hs_T_1" "S1.12hs_T_1" "S20.12hs_T_1"
## [154] "S3.12hs_T_1" "S4.12hs_T_1" "S5.12hs_T_1"
## [157] "S6.12hs_T_1" "S7.12hs_T_1" "S8.12hs_T_1"
## [160] "S9.12hs_T_1" "S11.18hs_T_1" "S12.18hs_T_1"
## [163] "S13.18hs_T_1" "S16.18hs_T_1" "S1.18hs_T_1"
## [166] "S20.18hs_T_1" "S5.18hs_T_1" "S6.18hs_T_1"
## [169] "S8.18hs_T_1" "S9.18hs_T_1" "Est.humedad_min_T_1"
## [172] "Est.humedad_med_T_1" "Est.humedad_max_T_1" "Est.temp_min_T_1"
## [175] "Est.temp_max_T_1" "Est.temp_med_T_1"
## Markov blanket of S18.min_t
## [1] "S18.max_T_2" "S5.max_T_2" "S18.media_T_2"
## [4] "S4.media_T_2" "S12.min_T_2" "S16.min_T_2"
## [7] "S18.min_T_2" "S12.15hs_T_2" "S13.15hs_T_2"
## [10] "S18.15hs_T_2" "S18.12hs_T_2" "S18.18hs_T_2"
## [13] "S1.18hs_T_2" "Est.temp_min_T_2" "Est.temp_max_T_2"
## [16] "S13.max_T_1" "S18.max_T_1" "S2.max_T_1"
## [19] "S18.media_T_1" "S20.media_T_1" "S8.media_T_1"
## [22] "S9.media_T_1" "S15.min_T_1" "S18.min_T_1"
## [25] "S18.15hs_T_1" "S18.12hs_T_1" "S4.12hs_T_1"
## [28] "S8.12hs_T_1" "S12.18hs_T_1" "S18.18hs_T_1"
## [31] "Est.humedad_min_T_1"
## Markov blanket of S19.min_t
## [1] "S19.max_T_2" "S19.media_T_2" "S4.media_T_2"
## [4] "S19.min_T_2" "S12.15hs_T_2" "S13.15hs_T_2"
## [7] "S14.15hs_T_2" "S17.15hs_T_2" "S19.15hs_T_2"
## [10] "S19.12hs_T_2" "S10.18hs_T_2" "S14.18hs_T_2"
## [13] "S19.18hs_T_2" "S4.18hs_T_2" "Est.temp_min_T_2"
## [16] "S19.max_T_1" "S13.media_T_1" "S19.media_T_1"
## [19] "S2.media_T_1" "S9.media_T_1" "S19.min_T_1"
## [22] "S1.min_T_1" "S19.15hs_T_1" "S19.12hs_T_1"
## [25] "S4.12hs_T_1" "S12.18hs_T_1" "S19.18hs_T_1"
## [28] "Est.humedad_min_T_1"
## Markov blanket of S1.min_t
## [1] "S16.max_T_2" "S1.max_T_2" "S4.max_T_2"
## [4] "S12.media_T_2" "S15.media_T_2" "S17.media_T_2"
## [7] "S1.media_T_2" "S4.media_T_2" "S6.media_T_2"
## [10] "S12.min_T_2" "S16.min_T_2" "S1.min_T_2"
## [13] "S13.15hs_T_2" "S17.15hs_T_2" "S1.15hs_T_2"
## [16] "S5.15hs_T_2" "S19.12hs_T_2" "S1.12hs_T_2"
## [19] "S14.18hs_T_2" "S1.18hs_T_2" "S6.18hs_T_2"
## [22] "S9.18hs_T_2" "Est.temp_min_T_2" "Est.temp_med_T_2"
## [25] "S1.max_T_1" "S2.max_T_1" "S9.max_T_1"
## [28] "S13.media_T_1" "S1.media_T_1" "S8.media_T_1"
## [31] "S9.media_T_1" "S12.min_T_1" "S1.min_T_1"
## [34] "S8.min_T_1" "S12.15hs_T_1" "S1.15hs_T_1"
## [37] "S16.12hs_T_1" "S1.12hs_T_1" "S4.12hs_T_1"
## [40] "S1.18hs_T_1" "S3.18hs_T_1" "S8.18hs_T_1"
## [43] "Est.humedad_med_T_1"
## Markov blanket of S20.min_t
## [1] "S10.max_T_2" "S11.max_T_2" "S12.max_T_2"
## [4] "S13.max_T_2" "S14.max_T_2" "S17.max_T_2"
## [7] "S1.max_T_2" "S20.max_T_2" "S2.max_T_2"
## [10] "S3.max_T_2" "S4.max_T_2" "S5.max_T_2"
## [13] "S6.max_T_2" "S8.max_T_2" "S9.max_T_2"
## [16] "S10.media_T_2" "S11.media_T_2" "S12.media_T_2"
## [19] "S13.media_T_2" "S15.media_T_2" "S17.media_T_2"
## [22] "S18.media_T_2" "S19.media_T_2" "S20.media_T_2"
## [25] "S2.media_T_2" "S3.media_T_2" "S4.media_T_2"
## [28] "S7.media_T_2" "S8.media_T_2" "S10.min_T_2"
## [31] "S11.min_T_2" "S12.min_T_2" "S14.min_T_2"
## [34] "S16.min_T_2" "S17.min_T_2" "S18.min_T_2"
## [37] "S20.min_T_2" "S2.min_T_2" "S3.min_T_2"
## [40] "S4.min_T_2" "S5.min_T_2" "S6.min_T_2"
## [43] "S7.min_T_2" "S8.min_T_2" "S9.min_T_2"
## [46] "S10.15hs_T_2" "S11.15hs_T_2" "S12.15hs_T_2"
## [49] "S13.15hs_T_2" "S14.15hs_T_2" "S15.15hs_T_2"
## [52] "S16.15hs_T_2" "S17.15hs_T_2" "S18.15hs_T_2"
## [55] "S19.15hs_T_2" "S1.15hs_T_2" "S20.15hs_T_2"
## [58] "S2.15hs_T_2" "S3.15hs_T_2" "S4.15hs_T_2"
## [61] "S5.15hs_T_2" "S6.15hs_T_2" "S7.15hs_T_2"
## [64] "S9.15hs_T_2" "S10.12hs_T_2" "S11.12hs_T_2"
## [67] "S12.12hs_T_2" "S13.12hs_T_2" "S14.12hs_T_2"
## [70] "S15.12hs_T_2" "S17.12hs_T_2" "S18.12hs_T_2"
## [73] "S19.12hs_T_2" "S1.12hs_T_2" "S20.12hs_T_2"
## [76] "S2.12hs_T_2" "S3.12hs_T_2" "S5.12hs_T_2"
## [79] "S7.12hs_T_2" "S8.12hs_T_2" "S9.12hs_T_2"
## [82] "S10.18hs_T_2" "S11.18hs_T_2" "S12.18hs_T_2"
## [85] "S13.18hs_T_2" "S14.18hs_T_2" "S15.18hs_T_2"
## [88] "S16.18hs_T_2" "S17.18hs_T_2" "S18.18hs_T_2"
## [91] "S19.18hs_T_2" "S1.18hs_T_2" "S20.18hs_T_2"
## [94] "S2.18hs_T_2" "S5.18hs_T_2" "S6.18hs_T_2"
## [97] "S7.18hs_T_2" "S8.18hs_T_2" "S9.18hs_T_2"
## [100] "Est.humedad_min_T_2" "Est.humedad_med_T_2" "Est.humedad_max_T_2"
## [103] "Est.temp_max_T_2" "Est.temp_med_T_2" "S10.max_T_1"
## [106] "S11.max_T_1" "S12.max_T_1" "S13.max_T_1"
## [109] "S14.max_T_1" "S15.max_T_1" "S17.max_T_1"
## [112] "S19.max_T_1" "S20.max_T_1" "S2.max_T_1"
## [115] "S3.max_T_1" "S4.max_T_1" "S5.max_T_1"
## [118] "S6.max_T_1" "S7.max_T_1" "S8.max_T_1"
## [121] "S10.media_T_1" "S11.media_T_1" "S12.media_T_1"
## [124] "S13.media_T_1" "S14.media_T_1" "S15.media_T_1"
## [127] "S16.media_T_1" "S17.media_T_1" "S18.media_T_1"
## [130] "S19.media_T_1" "S1.media_T_1" "S20.media_T_1"
## [133] "S2.media_T_1" "S3.media_T_1" "S4.media_T_1"
## [136] "S5.media_T_1" "S6.media_T_1" "S7.media_T_1"
## [139] "S8.media_T_1" "S9.media_T_1" "S12.min_T_1"
## [142] "S13.min_T_1" "S14.min_T_1" "S15.min_T_1"
## [145] "S16.min_T_1" "S17.min_T_1" "S18.min_T_1"
## [148] "S19.min_T_1" "S20.min_T_1" "S2.min_T_1"
## [151] "S3.min_T_1" "S4.min_T_1" "S5.min_T_1"
## [154] "S7.min_T_1" "S8.min_T_1" "S9.min_T_1"
## [157] "S10.15hs_T_1" "S11.15hs_T_1" "S13.15hs_T_1"
## [160] "S14.15hs_T_1" "S15.15hs_T_1" "S16.15hs_T_1"
## [163] "S19.15hs_T_1" "S20.15hs_T_1" "S2.15hs_T_1"
## [166] "S3.15hs_T_1" "S4.15hs_T_1" "S7.15hs_T_1"
## [169] "S8.15hs_T_1" "S9.15hs_T_1" "S10.12hs_T_1"
## [172] "S14.12hs_T_1" "S15.12hs_T_1" "S17.12hs_T_1"
## [175] "S19.12hs_T_1" "S1.12hs_T_1" "S20.12hs_T_1"
## [178] "S2.12hs_T_1" "S3.12hs_T_1" "S4.12hs_T_1"
## [181] "S5.12hs_T_1" "S6.12hs_T_1" "S7.12hs_T_1"
## [184] "S8.12hs_T_1" "S9.12hs_T_1" "S11.18hs_T_1"
## [187] "S13.18hs_T_1" "S17.18hs_T_1" "S18.18hs_T_1"
## [190] "S20.18hs_T_1" "S3.18hs_T_1" "S4.18hs_T_1"
## [193] "S5.18hs_T_1" "S7.18hs_T_1" "S8.18hs_T_1"
## [196] "Est.humedad_min_T_1" "Est.humedad_med_T_1" "Est.humedad_max_T_1"
## [199] "Est.temp_min_T_1" "Est.temp_max_T_1" "S10.min_t"
## [202] "S6.min_t" "S8.min_t"
## Markov blanket of S2.min_t
## [1] "S11.max_T_2" "S12.max_T_2" "S13.max_T_2"
## [4] "S14.max_T_2" "S15.max_T_2" "S16.max_T_2"
## [7] "S17.max_T_2" "S18.max_T_2" "S1.max_T_2"
## [10] "S20.max_T_2" "S2.max_T_2" "S3.max_T_2"
## [13] "S6.max_T_2" "S7.max_T_2" "S8.max_T_2"
## [16] "S10.media_T_2" "S11.media_T_2" "S12.media_T_2"
## [19] "S13.media_T_2" "S14.media_T_2" "S17.media_T_2"
## [22] "S18.media_T_2" "S1.media_T_2" "S20.media_T_2"
## [25] "S2.media_T_2" "S3.media_T_2" "S4.media_T_2"
## [28] "S5.media_T_2" "S6.media_T_2" "S7.media_T_2"
## [31] "S8.media_T_2" "S9.media_T_2" "S10.min_T_2"
## [34] "S11.min_T_2" "S12.min_T_2" "S13.min_T_2"
## [37] "S15.min_T_2" "S16.min_T_2" "S17.min_T_2"
## [40] "S18.min_T_2" "S1.min_T_2" "S20.min_T_2"
## [43] "S2.min_T_2" "S3.min_T_2" "S5.min_T_2"
## [46] "S6.min_T_2" "S7.min_T_2" "S8.min_T_2"
## [49] "S9.min_T_2" "S10.15hs_T_2" "S11.15hs_T_2"
## [52] "S12.15hs_T_2" "S13.15hs_T_2" "S16.15hs_T_2"
## [55] "S17.15hs_T_2" "S18.15hs_T_2" "S19.15hs_T_2"
## [58] "S1.15hs_T_2" "S20.15hs_T_2" "S2.15hs_T_2"
## [61] "S4.15hs_T_2" "S5.15hs_T_2" "S6.15hs_T_2"
## [64] "S9.15hs_T_2" "S10.12hs_T_2" "S11.12hs_T_2"
## [67] "S12.12hs_T_2" "S14.12hs_T_2" "S15.12hs_T_2"
## [70] "S17.12hs_T_2" "S18.12hs_T_2" "S19.12hs_T_2"
## [73] "S1.12hs_T_2" "S20.12hs_T_2" "S2.12hs_T_2"
## [76] "S5.12hs_T_2" "S7.12hs_T_2" "S8.12hs_T_2"
## [79] "S9.12hs_T_2" "S10.18hs_T_2" "S11.18hs_T_2"
## [82] "S12.18hs_T_2" "S13.18hs_T_2" "S14.18hs_T_2"
## [85] "S15.18hs_T_2" "S17.18hs_T_2" "S19.18hs_T_2"
## [88] "S1.18hs_T_2" "S2.18hs_T_2" "S3.18hs_T_2"
## [91] "S5.18hs_T_2" "S6.18hs_T_2" "S8.18hs_T_2"
## [94] "Est.temp_min_T_2" "Est.temp_max_T_2" "Est.temp_med_T_2"
## [97] "S11.max_T_1" "S12.max_T_1" "S13.max_T_1"
## [100] "S15.max_T_1" "S18.max_T_1" "S1.max_T_1"
## [103] "S20.max_T_1" "S2.max_T_1" "S4.max_T_1"
## [106] "S5.max_T_1" "S7.max_T_1" "S9.max_T_1"
## [109] "S13.media_T_1" "S15.media_T_1" "S16.media_T_1"
## [112] "S1.media_T_1" "S2.media_T_1" "S3.media_T_1"
## [115] "S4.media_T_1" "S5.media_T_1" "S8.media_T_1"
## [118] "S10.min_T_1" "S11.min_T_1" "S12.min_T_1"
## [121] "S13.min_T_1" "S14.min_T_1" "S16.min_T_1"
## [124] "S17.min_T_1" "S18.min_T_1" "S2.min_T_1"
## [127] "S4.min_T_1" "S6.min_T_1" "S8.min_T_1"
## [130] "S9.min_T_1" "S13.15hs_T_1" "S15.15hs_T_1"
## [133] "S16.15hs_T_1" "S18.15hs_T_1" "S19.15hs_T_1"
## [136] "S1.15hs_T_1" "S2.15hs_T_1" "S3.15hs_T_1"
## [139] "S4.15hs_T_1" "S5.15hs_T_1" "S8.15hs_T_1"
## [142] "S10.12hs_T_1" "S12.12hs_T_1" "S13.12hs_T_1"
## [145] "S14.12hs_T_1" "S15.12hs_T_1" "S1.12hs_T_1"
## [148] "S20.12hs_T_1" "S2.12hs_T_1" "S4.12hs_T_1"
## [151] "S5.12hs_T_1" "S6.12hs_T_1" "S7.12hs_T_1"
## [154] "S8.12hs_T_1" "S9.12hs_T_1" "S10.18hs_T_1"
## [157] "S11.18hs_T_1" "S12.18hs_T_1" "S13.18hs_T_1"
## [160] "S17.18hs_T_1" "S18.18hs_T_1" "S19.18hs_T_1"
## [163] "S1.18hs_T_1" "S2.18hs_T_1" "S3.18hs_T_1"
## [166] "S4.18hs_T_1" "S5.18hs_T_1" "S6.18hs_T_1"
## [169] "S7.18hs_T_1" "S8.18hs_T_1" "Est.humedad_min_T_1"
## [172] "Est.humedad_med_T_1" "Est.humedad_max_T_1" "Est.temp_min_T_1"
## [175] "Est.temp_max_T_1" "Est.temp_med_T_1"
## Markov blanket of S3.min_t
## [1] "S11.max_T_2" "S13.max_T_2" "S3.max_T_2"
## [4] "S12.media_T_2" "S20.media_T_2" "S3.media_T_2"
## [7] "S4.media_T_2" "S6.media_T_2" "S1.min_T_2"
## [10] "S2.min_T_2" "S3.min_T_2" "S8.min_T_2"
## [13] "S13.15hs_T_2" "S17.15hs_T_2" "S3.15hs_T_2"
## [16] "S5.15hs_T_2" "S19.12hs_T_2" "S3.12hs_T_2"
## [19] "S10.18hs_T_2" "S14.18hs_T_2" "S2.18hs_T_2"
## [22] "S3.18hs_T_2" "S4.18hs_T_2" "Est.temp_min_T_2"
## [25] "S2.max_T_1" "S3.max_T_1" "S13.media_T_1"
## [28] "S19.media_T_1" "S3.media_T_1" "S4.media_T_1"
## [31] "S5.media_T_1" "S9.media_T_1" "S12.min_T_1"
## [34] "S13.min_T_1" "S3.min_T_1" "S17.15hs_T_1"
## [37] "S1.15hs_T_1" "S3.15hs_T_1" "S3.12hs_T_1"
## [40] "S12.18hs_T_1" "S3.18hs_T_1" "Est.humedad_min_T_1"
## Markov blanket of S4.min_t
## [1] "S11.max_T_2" "S12.max_T_2" "S14.max_T_2"
## [4] "S16.max_T_2" "S17.max_T_2" "S18.max_T_2"
## [7] "S20.max_T_2" "S2.max_T_2" "S3.max_T_2"
## [10] "S4.max_T_2" "S5.max_T_2" "S6.max_T_2"
## [13] "S11.media_T_2" "S13.media_T_2" "S14.media_T_2"
## [16] "S15.media_T_2" "S17.media_T_2" "S1.media_T_2"
## [19] "S20.media_T_2" "S2.media_T_2" "S3.media_T_2"
## [22] "S4.media_T_2" "S7.media_T_2" "S11.min_T_2"
## [25] "S12.min_T_2" "S14.min_T_2" "S16.min_T_2"
## [28] "S18.min_T_2" "S19.min_T_2" "S20.min_T_2"
## [31] "S2.min_T_2" "S4.min_T_2" "S5.min_T_2"
## [34] "S6.min_T_2" "S7.min_T_2" "S9.min_T_2"
## [37] "S10.15hs_T_2" "S12.15hs_T_2" "S13.15hs_T_2"
## [40] "S14.15hs_T_2" "S15.15hs_T_2" "S16.15hs_T_2"
## [43] "S17.15hs_T_2" "S18.15hs_T_2" "S19.15hs_T_2"
## [46] "S3.15hs_T_2" "S4.15hs_T_2" "S5.15hs_T_2"
## [49] "S6.15hs_T_2" "S7.15hs_T_2" "S8.15hs_T_2"
## [52] "S10.12hs_T_2" "S11.12hs_T_2" "S12.12hs_T_2"
## [55] "S15.12hs_T_2" "S18.12hs_T_2" "S19.12hs_T_2"
## [58] "S1.12hs_T_2" "S3.12hs_T_2" "S4.12hs_T_2"
## [61] "S5.12hs_T_2" "S6.12hs_T_2" "S7.12hs_T_2"
## [64] "S8.12hs_T_2" "S9.12hs_T_2" "S10.18hs_T_2"
## [67] "S11.18hs_T_2" "S14.18hs_T_2" "S15.18hs_T_2"
## [70] "S17.18hs_T_2" "S18.18hs_T_2" "S1.18hs_T_2"
## [73] "S3.18hs_T_2" "S4.18hs_T_2" "S5.18hs_T_2"
## [76] "S6.18hs_T_2" "S7.18hs_T_2" "S8.18hs_T_2"
## [79] "S9.18hs_T_2" "Est.humedad_min_T_2" "Est.humedad_med_T_2"
## [82] "Est.temp_min_T_2" "S11.max_T_1" "S12.max_T_1"
## [85] "S13.max_T_1" "S14.max_T_1" "S15.max_T_1"
## [88] "S16.max_T_1" "S17.max_T_1" "S1.max_T_1"
## [91] "S20.max_T_1" "S2.max_T_1" "S3.max_T_1"
## [94] "S4.max_T_1" "S5.max_T_1" "S6.max_T_1"
## [97] "S7.max_T_1" "S8.max_T_1" "S9.max_T_1"
## [100] "S10.media_T_1" "S11.media_T_1" "S12.media_T_1"
## [103] "S13.media_T_1" "S14.media_T_1" "S15.media_T_1"
## [106] "S17.media_T_1" "S18.media_T_1" "S1.media_T_1"
## [109] "S20.media_T_1" "S3.media_T_1" "S4.media_T_1"
## [112] "S5.media_T_1" "S6.media_T_1" "S7.media_T_1"
## [115] "S8.media_T_1" "S9.media_T_1" "S10.min_T_1"
## [118] "S11.min_T_1" "S12.min_T_1" "S13.min_T_1"
## [121] "S14.min_T_1" "S17.min_T_1" "S18.min_T_1"
## [124] "S19.min_T_1" "S1.min_T_1" "S2.min_T_1"
## [127] "S4.min_T_1" "S5.min_T_1" "S6.min_T_1"
## [130] "S7.min_T_1" "S8.min_T_1" "S9.min_T_1"
## [133] "S10.15hs_T_1" "S11.15hs_T_1" "S13.15hs_T_1"
## [136] "S14.15hs_T_1" "S15.15hs_T_1" "S16.15hs_T_1"
## [139] "S18.15hs_T_1" "S1.15hs_T_1" "S20.15hs_T_1"
## [142] "S2.15hs_T_1" "S3.15hs_T_1" "S4.15hs_T_1"
## [145] "S5.15hs_T_1" "S6.15hs_T_1" "S8.15hs_T_1"
## [148] "S10.12hs_T_1" "S11.12hs_T_1" "S12.12hs_T_1"
## [151] "S14.12hs_T_1" "S15.12hs_T_1" "S19.12hs_T_1"
## [154] "S1.12hs_T_1" "S20.12hs_T_1" "S4.12hs_T_1"
## [157] "S5.12hs_T_1" "S6.12hs_T_1" "S7.12hs_T_1"
## [160] "S8.12hs_T_1" "S9.12hs_T_1" "S10.18hs_T_1"
## [163] "S11.18hs_T_1" "S13.18hs_T_1" "S14.18hs_T_1"
## [166] "S19.18hs_T_1" "S20.18hs_T_1" "S2.18hs_T_1"
## [169] "S3.18hs_T_1" "S4.18hs_T_1" "S5.18hs_T_1"
## [172] "S6.18hs_T_1" "S7.18hs_T_1" "S8.18hs_T_1"
## [175] "S9.18hs_T_1" "Est.temp_max_T_1"
## Markov blanket of S5.min_t
## [1] "S10.max_T_2" "S13.max_T_2" "S14.max_T_2"
## [4] "S15.max_T_2" "S16.max_T_2" "S17.max_T_2"
## [7] "S18.max_T_2" "S19.max_T_2" "S1.max_T_2"
## [10] "S20.max_T_2" "S3.max_T_2" "S4.max_T_2"
## [13] "S5.max_T_2" "S6.max_T_2" "S7.max_T_2"
## [16] "S8.max_T_2" "S9.max_T_2" "S10.media_T_2"
## [19] "S11.media_T_2" "S12.media_T_2" "S13.media_T_2"
## [22] "S15.media_T_2" "S16.media_T_2" "S17.media_T_2"
## [25] "S18.media_T_2" "S19.media_T_2" "S20.media_T_2"
## [28] "S2.media_T_2" "S3.media_T_2" "S4.media_T_2"
## [31] "S5.media_T_2" "S6.media_T_2" "S8.media_T_2"
## [34] "S9.media_T_2" "S10.min_T_2" "S11.min_T_2"
## [37] "S12.min_T_2" "S13.min_T_2" "S14.min_T_2"
## [40] "S15.min_T_2" "S16.min_T_2" "S17.min_T_2"
## [43] "S18.min_T_2" "S19.min_T_2" "S1.min_T_2"
## [46] "S20.min_T_2" "S2.min_T_2" "S3.min_T_2"
## [49] "S4.min_T_2" "S5.min_T_2" "S6.min_T_2"
## [52] "S7.min_T_2" "S8.min_T_2" "S9.min_T_2"
## [55] "S10.15hs_T_2" "S11.15hs_T_2" "S12.15hs_T_2"
## [58] "S13.15hs_T_2" "S15.15hs_T_2" "S16.15hs_T_2"
## [61] "S17.15hs_T_2" "S18.15hs_T_2" "S19.15hs_T_2"
## [64] "S1.15hs_T_2" "S20.15hs_T_2" "S3.15hs_T_2"
## [67] "S4.15hs_T_2" "S5.15hs_T_2" "S6.15hs_T_2"
## [70] "S7.15hs_T_2" "S8.15hs_T_2" "S9.15hs_T_2"
## [73] "S10.12hs_T_2" "S11.12hs_T_2" "S12.12hs_T_2"
## [76] "S13.12hs_T_2" "S14.12hs_T_2" "S15.12hs_T_2"
## [79] "S16.12hs_T_2" "S18.12hs_T_2" "S1.12hs_T_2"
## [82] "S20.12hs_T_2" "S2.12hs_T_2" "S3.12hs_T_2"
## [85] "S4.12hs_T_2" "S5.12hs_T_2" "S6.12hs_T_2"
## [88] "S7.12hs_T_2" "S8.12hs_T_2" "S9.12hs_T_2"
## [91] "S10.18hs_T_2" "S11.18hs_T_2" "S12.18hs_T_2"
## [94] "S14.18hs_T_2" "S15.18hs_T_2" "S16.18hs_T_2"
## [97] "S17.18hs_T_2" "S18.18hs_T_2" "S1.18hs_T_2"
## [100] "S20.18hs_T_2" "S2.18hs_T_2" "S3.18hs_T_2"
## [103] "S4.18hs_T_2" "S5.18hs_T_2" "S6.18hs_T_2"
## [106] "S7.18hs_T_2" "S8.18hs_T_2" "S9.18hs_T_2"
## [109] "Est.humedad_med_T_2" "Est.humedad_max_T_2" "Est.temp_max_T_2"
## [112] "S11.max_T_1" "S12.max_T_1" "S13.max_T_1"
## [115] "S14.max_T_1" "S15.max_T_1" "S16.max_T_1"
## [118] "S17.max_T_1" "S18.max_T_1" "S19.max_T_1"
## [121] "S20.max_T_1" "S2.max_T_1" "S3.max_T_1"
## [124] "S4.max_T_1" "S5.max_T_1" "S6.max_T_1"
## [127] "S8.max_T_1" "S9.max_T_1" "S3.media_T_1"
## [130] "S5.media_T_1" "S8.media_T_1" "S9.media_T_1"
## [133] "S12.min_T_1" "S14.min_T_1" "S16.min_T_1"
## [136] "S17.min_T_1" "S18.min_T_1" "S19.min_T_1"
## [139] "S1.min_T_1" "S20.min_T_1" "S3.min_T_1"
## [142] "S5.min_T_1" "S6.min_T_1" "S8.min_T_1"
## [145] "S9.min_T_1" "S10.15hs_T_1" "S11.15hs_T_1"
## [148] "S12.15hs_T_1" "S14.15hs_T_1" "S15.15hs_T_1"
## [151] "S16.15hs_T_1" "S17.15hs_T_1" "S18.15hs_T_1"
## [154] "S19.15hs_T_1" "S1.15hs_T_1" "S20.15hs_T_1"
## [157] "S2.15hs_T_1" "S3.15hs_T_1" "S4.15hs_T_1"
## [160] "S5.15hs_T_1" "S6.15hs_T_1" "S7.15hs_T_1"
## [163] "S8.15hs_T_1" "S9.15hs_T_1" "S10.12hs_T_1"
## [166] "S12.12hs_T_1" "S13.12hs_T_1" "S14.12hs_T_1"
## [169] "S15.12hs_T_1" "S16.12hs_T_1" "S18.12hs_T_1"
## [172] "S19.12hs_T_1" "S1.12hs_T_1" "S20.12hs_T_1"
## [175] "S2.12hs_T_1" "S4.12hs_T_1" "S5.12hs_T_1"
## [178] "S7.12hs_T_1" "S8.12hs_T_1" "S9.12hs_T_1"
## [181] "S10.18hs_T_1" "S11.18hs_T_1" "S12.18hs_T_1"
## [184] "S13.18hs_T_1" "S14.18hs_T_1" "S15.18hs_T_1"
## [187] "S16.18hs_T_1" "S17.18hs_T_1" "S18.18hs_T_1"
## [190] "S19.18hs_T_1" "S20.18hs_T_1" "S4.18hs_T_1"
## [193] "S5.18hs_T_1" "S6.18hs_T_1" "S7.18hs_T_1"
## [196] "S8.18hs_T_1" "Est.humedad_min_T_1" "Est.humedad_max_T_1"
## [199] "Est.temp_min_T_1" "Est.temp_max_T_1" "S14.min_t"
## Markov blanket of S6.min_t
## [1] "S10.max_T_2" "S11.max_T_2" "S12.max_T_2"
## [4] "S13.max_T_2" "S14.max_T_2" "S16.max_T_2"
## [7] "S17.max_T_2" "S19.max_T_2" "S1.max_T_2"
## [10] "S20.max_T_2" "S2.max_T_2" "S5.max_T_2"
## [13] "S6.max_T_2" "S7.max_T_2" "S9.max_T_2"
## [16] "S12.media_T_2" "S13.media_T_2" "S16.media_T_2"
## [19] "S17.media_T_2" "S18.media_T_2" "S20.media_T_2"
## [22] "S2.media_T_2" "S4.media_T_2" "S5.media_T_2"
## [25] "S6.media_T_2" "S7.media_T_2" "S8.media_T_2"
## [28] "S9.media_T_2" "S10.min_T_2" "S11.min_T_2"
## [31] "S13.min_T_2" "S14.min_T_2" "S16.min_T_2"
## [34] "S17.min_T_2" "S18.min_T_2" "S1.min_T_2"
## [37] "S2.min_T_2" "S4.min_T_2" "S5.min_T_2"
## [40] "S6.min_T_2" "S7.min_T_2" "S8.min_T_2"
## [43] "S9.min_T_2" "S10.15hs_T_2" "S11.15hs_T_2"
## [46] "S12.15hs_T_2" "S13.15hs_T_2" "S14.15hs_T_2"
## [49] "S17.15hs_T_2" "S18.15hs_T_2" "S19.15hs_T_2"
## [52] "S20.15hs_T_2" "S2.15hs_T_2" "S3.15hs_T_2"
## [55] "S4.15hs_T_2" "S5.15hs_T_2" "S6.15hs_T_2"
## [58] "S8.15hs_T_2" "S10.12hs_T_2" "S11.12hs_T_2"
## [61] "S13.12hs_T_2" "S14.12hs_T_2" "S16.12hs_T_2"
## [64] "S17.12hs_T_2" "S18.12hs_T_2" "S19.12hs_T_2"
## [67] "S1.12hs_T_2" "S20.12hs_T_2" "S2.12hs_T_2"
## [70] "S3.12hs_T_2" "S5.12hs_T_2" "S6.12hs_T_2"
## [73] "S7.12hs_T_2" "S8.12hs_T_2" "S9.12hs_T_2"
## [76] "S10.18hs_T_2" "S12.18hs_T_2" "S13.18hs_T_2"
## [79] "S14.18hs_T_2" "S15.18hs_T_2" "S16.18hs_T_2"
## [82] "S17.18hs_T_2" "S1.18hs_T_2" "S20.18hs_T_2"
## [85] "S2.18hs_T_2" "S3.18hs_T_2" "S4.18hs_T_2"
## [88] "S5.18hs_T_2" "S6.18hs_T_2" "S7.18hs_T_2"
## [91] "S8.18hs_T_2" "S9.18hs_T_2" "Est.humedad_min_T_2"
## [94] "Est.humedad_med_T_2" "Est.humedad_max_T_2" "S10.max_T_1"
## [97] "S11.max_T_1" "S12.max_T_1" "S13.max_T_1"
## [100] "S14.max_T_1" "S15.max_T_1" "S16.max_T_1"
## [103] "S17.max_T_1" "S19.max_T_1" "S20.max_T_1"
## [106] "S2.max_T_1" "S3.max_T_1" "S4.max_T_1"
## [109] "S5.max_T_1" "S6.max_T_1" "S7.max_T_1"
## [112] "S8.max_T_1" "S9.max_T_1" "S10.media_T_1"
## [115] "S11.media_T_1" "S15.media_T_1" "S18.media_T_1"
## [118] "S1.media_T_1" "S20.media_T_1" "S2.media_T_1"
## [121] "S3.media_T_1" "S4.media_T_1" "S5.media_T_1"
## [124] "S6.media_T_1" "S7.media_T_1" "S8.media_T_1"
## [127] "S10.min_T_1" "S11.min_T_1" "S12.min_T_1"
## [130] "S13.min_T_1" "S15.min_T_1" "S16.min_T_1"
## [133] "S18.min_T_1" "S19.min_T_1" "S1.min_T_1"
## [136] "S20.min_T_1" "S2.min_T_1" "S3.min_T_1"
## [139] "S4.min_T_1" "S5.min_T_1" "S6.min_T_1"
## [142] "S7.min_T_1" "S8.min_T_1" "S10.15hs_T_1"
## [145] "S11.15hs_T_1" "S14.15hs_T_1" "S16.15hs_T_1"
## [148] "S19.15hs_T_1" "S20.15hs_T_1" "S2.15hs_T_1"
## [151] "S3.15hs_T_1" "S4.15hs_T_1" "S5.15hs_T_1"
## [154] "S6.15hs_T_1" "S9.15hs_T_1" "S10.12hs_T_1"
## [157] "S12.12hs_T_1" "S17.12hs_T_1" "S18.12hs_T_1"
## [160] "S1.12hs_T_1" "S20.12hs_T_1" "S2.12hs_T_1"
## [163] "S3.12hs_T_1" "S4.12hs_T_1" "S6.12hs_T_1"
## [166] "S7.12hs_T_1" "S8.12hs_T_1" "S10.18hs_T_1"
## [169] "S11.18hs_T_1" "S12.18hs_T_1" "S13.18hs_T_1"
## [172] "S14.18hs_T_1" "S17.18hs_T_1" "S19.18hs_T_1"
## [175] "S1.18hs_T_1" "S20.18hs_T_1" "S2.18hs_T_1"
## [178] "S3.18hs_T_1" "S4.18hs_T_1" "S5.18hs_T_1"
## [181] "S6.18hs_T_1" "S7.18hs_T_1" "S8.18hs_T_1"
## [184] "S9.18hs_T_1" "Est.humedad_min_T_1" "Est.humedad_med_T_1"
## [187] "Est.temp_min_T_1" "Est.temp_max_T_1" "S10.min_t"
## [190] "S11.min_t" "S20.min_t"
## Markov blanket of S7.min_t
## [1] "S11.max_T_2" "S14.max_T_2" "S20.max_T_2"
## [4] "S7.max_T_2" "S10.media_T_2" "S12.media_T_2"
## [7] "S17.media_T_2" "S6.media_T_2" "S7.media_T_2"
## [10] "S7.min_T_2" "S12.15hs_T_2" "S13.15hs_T_2"
## [13] "S17.15hs_T_2" "S5.15hs_T_2" "S7.15hs_T_2"
## [16] "S4.12hs_T_2" "S7.12hs_T_2" "S12.18hs_T_2"
## [19] "S14.18hs_T_2" "S15.18hs_T_2" "S1.18hs_T_2"
## [22] "S7.18hs_T_2" "Est.temp_min_T_2" "S13.max_T_1"
## [25] "S2.max_T_1" "S3.max_T_1" "S7.max_T_1"
## [28] "S13.media_T_1" "S3.media_T_1" "S7.media_T_1"
## [31] "S8.media_T_1" "S9.media_T_1" "S7.min_T_1"
## [34] "S12.15hs_T_1" "S3.15hs_T_1" "S7.15hs_T_1"
## [37] "S2.12hs_T_1" "S4.12hs_T_1" "S7.12hs_T_1"
## [40] "S12.18hs_T_1" "S7.18hs_T_1" "Est.humedad_min_T_1"
## Markov blanket of S8.min_t
## [1] "S11.max_T_2" "S13.max_T_2" "S14.max_T_2"
## [4] "S15.max_T_2" "S16.max_T_2" "S1.max_T_2"
## [7] "S20.max_T_2" "S2.max_T_2" "S3.max_T_2"
## [10] "S5.max_T_2" "S6.max_T_2" "S7.max_T_2"
## [13] "S8.max_T_2" "S9.max_T_2" "S10.media_T_2"
## [16] "S11.media_T_2" "S13.media_T_2" "S14.media_T_2"
## [19] "S15.media_T_2" "S16.media_T_2" "S17.media_T_2"
## [22] "S19.media_T_2" "S20.media_T_2" "S2.media_T_2"
## [25] "S3.media_T_2" "S4.media_T_2" "S5.media_T_2"
## [28] "S6.media_T_2" "S7.media_T_2" "S8.media_T_2"
## [31] "S9.media_T_2" "S12.min_T_2" "S14.min_T_2"
## [34] "S16.min_T_2" "S18.min_T_2" "S19.min_T_2"
## [37] "S1.min_T_2" "S20.min_T_2" "S2.min_T_2"
## [40] "S3.min_T_2" "S4.min_T_2" "S5.min_T_2"
## [43] "S6.min_T_2" "S8.min_T_2" "S9.min_T_2"
## [46] "S10.15hs_T_2" "S11.15hs_T_2" "S12.15hs_T_2"
## [49] "S13.15hs_T_2" "S14.15hs_T_2" "S17.15hs_T_2"
## [52] "S18.15hs_T_2" "S19.15hs_T_2" "S20.15hs_T_2"
## [55] "S2.15hs_T_2" "S3.15hs_T_2" "S4.15hs_T_2"
## [58] "S5.15hs_T_2" "S6.15hs_T_2" "S7.15hs_T_2"
## [61] "S8.15hs_T_2" "S9.15hs_T_2" "S10.12hs_T_2"
## [64] "S12.12hs_T_2" "S13.12hs_T_2" "S14.12hs_T_2"
## [67] "S15.12hs_T_2" "S17.12hs_T_2" "S18.12hs_T_2"
## [70] "S19.12hs_T_2" "S1.12hs_T_2" "S20.12hs_T_2"
## [73] "S3.12hs_T_2" "S5.12hs_T_2" "S6.12hs_T_2"
## [76] "S7.12hs_T_2" "S8.12hs_T_2" "S9.12hs_T_2"
## [79] "S10.18hs_T_2" "S11.18hs_T_2" "S12.18hs_T_2"
## [82] "S14.18hs_T_2" "S15.18hs_T_2" "S16.18hs_T_2"
## [85] "S18.18hs_T_2" "S1.18hs_T_2" "S20.18hs_T_2"
## [88] "S2.18hs_T_2" "S3.18hs_T_2" "S4.18hs_T_2"
## [91] "S5.18hs_T_2" "S6.18hs_T_2" "S7.18hs_T_2"
## [94] "S8.18hs_T_2" "S9.18hs_T_2" "Est.humedad_med_T_2"
## [97] "Est.humedad_max_T_2" "Est.temp_max_T_2" "Est.temp_med_T_2"
## [100] "S12.max_T_1" "S14.max_T_1" "S15.max_T_1"
## [103] "S17.max_T_1" "S18.max_T_1" "S1.max_T_1"
## [106] "S2.max_T_1" "S3.max_T_1" "S4.max_T_1"
## [109] "S6.max_T_1" "S7.max_T_1" "S8.max_T_1"
## [112] "S9.max_T_1" "S10.media_T_1" "S11.media_T_1"
## [115] "S13.media_T_1" "S14.media_T_1" "S15.media_T_1"
## [118] "S16.media_T_1" "S17.media_T_1" "S19.media_T_1"
## [121] "S20.media_T_1" "S3.media_T_1" "S4.media_T_1"
## [124] "S5.media_T_1" "S6.media_T_1" "S7.media_T_1"
## [127] "S8.media_T_1" "S9.media_T_1" "S10.min_T_1"
## [130] "S11.min_T_1" "S12.min_T_1" "S13.min_T_1"
## [133] "S14.min_T_1" "S15.min_T_1" "S16.min_T_1"
## [136] "S17.min_T_1" "S18.min_T_1" "S19.min_T_1"
## [139] "S1.min_T_1" "S3.min_T_1" "S8.min_T_1"
## [142] "S10.15hs_T_1" "S11.15hs_T_1" "S12.15hs_T_1"
## [145] "S13.15hs_T_1" "S14.15hs_T_1" "S15.15hs_T_1"
## [148] "S1.15hs_T_1" "S20.15hs_T_1" "S2.15hs_T_1"
## [151] "S3.15hs_T_1" "S7.15hs_T_1" "S8.15hs_T_1"
## [154] "S9.15hs_T_1" "S10.12hs_T_1" "S11.12hs_T_1"
## [157] "S12.12hs_T_1" "S14.12hs_T_1" "S15.12hs_T_1"
## [160] "S16.12hs_T_1" "S19.12hs_T_1" "S20.12hs_T_1"
## [163] "S3.12hs_T_1" "S4.12hs_T_1" "S5.12hs_T_1"
## [166] "S6.12hs_T_1" "S7.12hs_T_1" "S8.12hs_T_1"
## [169] "S10.18hs_T_1" "S12.18hs_T_1" "S16.18hs_T_1"
## [172] "S17.18hs_T_1" "S19.18hs_T_1" "S20.18hs_T_1"
## [175] "S2.18hs_T_1" "S5.18hs_T_1" "S6.18hs_T_1"
## [178] "S7.18hs_T_1" "S8.18hs_T_1" "S9.18hs_T_1"
## [181] "Est.humedad_min_T_1" "Est.humedad_med_T_1" "Est.humedad_max_T_1"
## [184] "Est.temp_min_T_1" "Est.temp_max_T_1" "S20.min_t"
## Markov blanket of S9.min_t
## [1] "S10.max_T_2" "S11.max_T_2" "S13.max_T_2"
## [4] "S14.max_T_2" "S15.max_T_2" "S17.max_T_2"
## [7] "S19.max_T_2" "S20.max_T_2" "S2.max_T_2"
## [10] "S5.max_T_2" "S6.max_T_2" "S8.max_T_2"
## [13] "S9.max_T_2" "S10.media_T_2" "S11.media_T_2"
## [16] "S12.media_T_2" "S13.media_T_2" "S17.media_T_2"
## [19] "S18.media_T_2" "S19.media_T_2" "S4.media_T_2"
## [22] "S6.media_T_2" "S7.media_T_2" "S8.media_T_2"
## [25] "S9.media_T_2" "S10.min_T_2" "S11.min_T_2"
## [28] "S12.min_T_2" "S14.min_T_2" "S15.min_T_2"
## [31] "S16.min_T_2" "S17.min_T_2" "S18.min_T_2"
## [34] "S19.min_T_2" "S1.min_T_2" "S20.min_T_2"
## [37] "S3.min_T_2" "S5.min_T_2" "S6.min_T_2"
## [40] "S7.min_T_2" "S9.min_T_2" "S10.15hs_T_2"
## [43] "S11.15hs_T_2" "S12.15hs_T_2" "S13.15hs_T_2"
## [46] "S16.15hs_T_2" "S17.15hs_T_2" "S18.15hs_T_2"
## [49] "S1.15hs_T_2" "S20.15hs_T_2" "S2.15hs_T_2"
## [52] "S4.15hs_T_2" "S6.15hs_T_2" "S9.15hs_T_2"
## [55] "S11.12hs_T_2" "S12.12hs_T_2" "S16.12hs_T_2"
## [58] "S17.12hs_T_2" "S18.12hs_T_2" "S19.12hs_T_2"
## [61] "S1.12hs_T_2" "S20.12hs_T_2" "S2.12hs_T_2"
## [64] "S3.12hs_T_2" "S4.12hs_T_2" "S5.12hs_T_2"
## [67] "S7.12hs_T_2" "S9.12hs_T_2" "S10.18hs_T_2"
## [70] "S12.18hs_T_2" "S13.18hs_T_2" "S14.18hs_T_2"
## [73] "S15.18hs_T_2" "S17.18hs_T_2" "S18.18hs_T_2"
## [76] "S19.18hs_T_2" "S1.18hs_T_2" "S20.18hs_T_2"
## [79] "S3.18hs_T_2" "S5.18hs_T_2" "S6.18hs_T_2"
## [82] "S7.18hs_T_2" "S9.18hs_T_2" "Est.humedad_min_T_2"
## [85] "Est.temp_min_T_2" "Est.temp_max_T_2" "S11.max_T_1"
## [88] "S12.max_T_1" "S13.max_T_1" "S14.max_T_1"
## [91] "S16.max_T_1" "S17.max_T_1" "S19.max_T_1"
## [94] "S1.max_T_1" "S20.max_T_1" "S2.max_T_1"
## [97] "S4.max_T_1" "S5.max_T_1" "S6.max_T_1"
## [100] "S7.max_T_1" "S8.max_T_1" "S9.max_T_1"
## [103] "S10.media_T_1" "S11.media_T_1" "S12.media_T_1"
## [106] "S13.media_T_1" "S14.media_T_1" "S16.media_T_1"
## [109] "S17.media_T_1" "S19.media_T_1" "S1.media_T_1"
## [112] "S20.media_T_1" "S2.media_T_1" "S3.media_T_1"
## [115] "S4.media_T_1" "S5.media_T_1" "S6.media_T_1"
## [118] "S7.media_T_1" "S8.media_T_1" "S9.media_T_1"
## [121] "S10.min_T_1" "S11.min_T_1" "S12.min_T_1"
## [124] "S13.min_T_1" "S14.min_T_1" "S16.min_T_1"
## [127] "S19.min_T_1" "S20.min_T_1" "S2.min_T_1"
## [130] "S4.min_T_1" "S5.min_T_1" "S6.min_T_1"
## [133] "S8.min_T_1" "S9.min_T_1" "S10.15hs_T_1"
## [136] "S11.15hs_T_1" "S12.15hs_T_1" "S13.15hs_T_1"
## [139] "S16.15hs_T_1" "S20.15hs_T_1" "S3.15hs_T_1"
## [142] "S4.15hs_T_1" "S5.15hs_T_1" "S8.15hs_T_1"
## [145] "S9.15hs_T_1" "S11.12hs_T_1" "S13.12hs_T_1"
## [148] "S14.12hs_T_1" "S15.12hs_T_1" "S16.12hs_T_1"
## [151] "S17.12hs_T_1" "S18.12hs_T_1" "S19.12hs_T_1"
## [154] "S1.12hs_T_1" "S20.12hs_T_1" "S2.12hs_T_1"
## [157] "S3.12hs_T_1" "S6.12hs_T_1" "S7.12hs_T_1"
## [160] "S8.12hs_T_1" "S9.12hs_T_1" "S10.18hs_T_1"
## [163] "S13.18hs_T_1" "S17.18hs_T_1" "S20.18hs_T_1"
## [166] "S2.18hs_T_1" "S3.18hs_T_1" "S4.18hs_T_1"
## [169] "S5.18hs_T_1" "S6.18hs_T_1" "S7.18hs_T_1"
## [172] "S8.18hs_T_1" "S9.18hs_T_1" "Est.humedad_min_T_1"
## [175] "Est.humedad_med_T_1" "Est.temp_max_T_1"Predicciones, evaluación en conjunto de testeo, caso regresión predicción temperaturas
df_res <- errors_regression(pred_sensores, fitted, test.set, verbose = FALSE)## Testing on S10.min_t
## Testing on S11.min_t
## Testing on S12.min_t
## Testing on S13.min_t
## Testing on S14.min_t
## Testing on S15.min_t
## Testing on S16.min_t
## Testing on S18.min_t
## Testing on S19.min_t
## Testing on S1.min_t
## Testing on S20.min_t
## Testing on S2.min_t
## Testing on S3.min_t
## Testing on S4.min_t
## Testing on S5.min_t
## Testing on S6.min_t
## Testing on S7.min_t
## Testing on S8.min_t
## Testing on S9.min_tdf_res## Variable ME RMSE MAE
## 1 S10.min_t 3.60600518024786 8.7894969590099 6.99916523154261
## 2 S11.min_t 4.88605119295279 10.7624676290499 8.09751638018731
## 3 S12.min_t 3.88066561273278 6.14419442362713 5.01479303477757
## 4 S13.min_t 9.24365769760631 13.1203965963704 10.7540553306959
## 5 S14.min_t -0.246110437194196 5.37040313778999 4.28208970527996
## 6 S15.min_t 8.00265403810435 13.0637337177942 10.7782771480533
## 7 S16.min_t 6.00272335353905 10.8123512058199 8.47588500539109
## 8 S18.min_t -0.249872162007854 3.31128335083729 2.67294035343279
## 9 S19.min_t 1.33117974583723 3.55845612354867 2.84270699960875
## 10 S1.min_t 0.564225915337782 3.76013108078897 2.96490586839661
## 11 S20.min_t 0.0403139508040176 6.82219446139092 5.2745118012074
## 12 S2.min_t 5.44785216657317 10.963686608273 8.64514580240215
## 13 S3.min_t 3.22537687915933 5.02068740939622 4.13141201530236
## 14 S4.min_t -1.08907587356427 8.54976375211855 6.78458991309805
## 15 S5.min_t 0.147638587509107 3.88034659553729 3.02941125201876
## 16 S6.min_t 2.75219381465485 8.07541099792463 6.4420713130876
## 17 S7.min_t 2.09634850650473 4.55951819082164 3.67845685319888
## 18 S8.min_t 3.29354170697762 9.43608566062138 7.42711789578608
## 19 S9.min_t 3.1301609657569 9.87771508999122 8.09945106515454
## MPE MAPE
## 1 Inf Inf
## 2 -Inf Inf
## 3 NaN Inf
## 4 NaN Inf
## 5 NaN Inf
## 6 66.0838225525667 286.419095801187
## 7 NaN Inf
## 8 -Inf Inf
## 9 NaN Inf
## 10 -Inf Inf
## 11 -Inf Inf
## 12 Inf Inf
## 13 Inf Inf
## 14 NaN Inf
## 15 -Inf Inf
## 16 NaN Inf
## 17 -Inf Inf
## 18 NaN Inf
## 19 NaN Infplots de R squared
r2_plots_inline(pred_sensores, fitted, test.set)
llamar confusionMatrix de caret, pasar primero “a factor of predicted classes, then a factor of classes to be used as the true results
breaks.binario <- c(-10,0,50) # caso Helada y no helada
my.breaks <- c(-10,-5,0,2,5,10,50)Caso binario: helada o no helada
conf_matrix_binario = conf_matrix(fitted,pred_sensores,test.set, breaks.binario)## Variable S10.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 11 39
## (0,50] 8 93
##
## Accuracy : 0.6887
## 95% CI : (0.6084, 0.7615)
## No Information Rate : 0.8742
## P-Value [Acc > NIR] : 1
##
## Kappa : 0.1669
## Mcnemar's Test P-Value : 1.209e-05
##
## Sensitivity : 0.57895
## Specificity : 0.70455
## Pos Pred Value : 0.22000
## Neg Pred Value : 0.92079
## Prevalence : 0.12583
## Detection Rate : 0.07285
## Detection Prevalence : 0.33113
## Balanced Accuracy : 0.64175
##
## 'Positive' Class : (-10,0]
##
## Variable S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 12 38
## (0,50] 6 86
##
## Accuracy : 0.6901
## 95% CI : (0.6072, 0.765)
## No Information Rate : 0.8732
## P-Value [Acc > NIR] : 1
##
## Kappa : 0.2047
## Mcnemar's Test P-Value : 2.962e-06
##
## Sensitivity : 0.66667
## Specificity : 0.69355
## Pos Pred Value : 0.24000
## Neg Pred Value : 0.93478
## Prevalence : 0.12676
## Detection Rate : 0.08451
## Detection Prevalence : 0.35211
## Balanced Accuracy : 0.68011
##
## 'Positive' Class : (-10,0]
##
## Variable S12.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 15 23
## (0,50] 4 112
##
## Accuracy : 0.8247
## 95% CI : (0.7553, 0.8812)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.977182
##
## Kappa : 0.4331
## Mcnemar's Test P-Value : 0.000532
##
## Sensitivity : 0.7895
## Specificity : 0.8296
## Pos Pred Value : 0.3947
## Neg Pred Value : 0.9655
## Prevalence : 0.1234
## Detection Rate : 0.0974
## Detection Prevalence : 0.2468
## Balanced Accuracy : 0.8096
##
## 'Positive' Class : (-10,0]
##
## Variable S13.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 5 55
## (0,50] 8 60
##
## Accuracy : 0.5078
## 95% CI : (0.418, 0.5972)
## No Information Rate : 0.8984
## P-Value [Acc > NIR] : 1
##
## Kappa : -0.036
## Mcnemar's Test P-Value : 6.814e-09
##
## Sensitivity : 0.38462
## Specificity : 0.52174
## Pos Pred Value : 0.08333
## Neg Pred Value : 0.88235
## Prevalence : 0.10156
## Detection Rate : 0.03906
## Detection Prevalence : 0.46875
## Balanced Accuracy : 0.45318
##
## 'Positive' Class : (-10,0]
##
## Variable S14.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 13 15
## (0,50] 6 120
##
## Accuracy : 0.8636
## 95% CI : (0.7991, 0.9136)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.73622
##
## Kappa : 0.4762
## Mcnemar's Test P-Value : 0.08086
##
## Sensitivity : 0.68421
## Specificity : 0.88889
## Pos Pred Value : 0.46429
## Neg Pred Value : 0.95238
## Prevalence : 0.12338
## Detection Rate : 0.08442
## Detection Prevalence : 0.18182
## Balanced Accuracy : 0.78655
##
## 'Positive' Class : (-10,0]
##
## Variable S15.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 8 45
## (0,50] 4 67
##
## Accuracy : 0.6048
## 95% CI : (0.5131, 0.6914)
## No Information Rate : 0.9032
## P-Value [Acc > NIR] : 1
##
## Kappa : 0.1049
## Mcnemar's Test P-Value : 1.102e-08
##
## Sensitivity : 0.66667
## Specificity : 0.59821
## Pos Pred Value : 0.15094
## Neg Pred Value : 0.94366
## Prevalence : 0.09677
## Detection Rate : 0.06452
## Detection Prevalence : 0.42742
## Balanced Accuracy : 0.63244
##
## 'Positive' Class : (-10,0]
##
## Variable S16.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 7 36
## (0,50] 3 87
##
## Accuracy : 0.7068
## 95% CI : (0.6216, 0.7825)
## No Information Rate : 0.9248
## P-Value [Acc > NIR] : 1
##
## Kappa : 0.1619
## Mcnemar's Test P-Value : 2.99e-07
##
## Sensitivity : 0.70000
## Specificity : 0.70732
## Pos Pred Value : 0.16279
## Neg Pred Value : 0.96667
## Prevalence : 0.07519
## Detection Rate : 0.05263
## Detection Prevalence : 0.32331
## Balanced Accuracy : 0.70366
##
## 'Positive' Class : (-10,0]
##
## Variable S18.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 7 3
## (0,50] 12 132
##
## Accuracy : 0.9026
## 95% CI : (0.8444, 0.9445)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.19770
##
## Kappa : 0.4347
## Mcnemar's Test P-Value : 0.03887
##
## Sensitivity : 0.36842
## Specificity : 0.97778
## Pos Pred Value : 0.70000
## Neg Pred Value : 0.91667
## Prevalence : 0.12338
## Detection Rate : 0.04545
## Detection Prevalence : 0.06494
## Balanced Accuracy : 0.67310
##
## 'Positive' Class : (-10,0]
##
## Variable S19.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 12 8
## (0,50] 7 127
##
## Accuracy : 0.9026
## 95% CI : (0.8444, 0.9445)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.1977
##
## Kappa : 0.5597
## Mcnemar's Test P-Value : 1.0000
##
## Sensitivity : 0.63158
## Specificity : 0.94074
## Pos Pred Value : 0.60000
## Neg Pred Value : 0.94776
## Prevalence : 0.12338
## Detection Rate : 0.07792
## Detection Prevalence : 0.12987
## Balanced Accuracy : 0.78616
##
## 'Positive' Class : (-10,0]
##
## Variable S1.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 14 8
## (0,50] 5 127
##
## Accuracy : 0.9156
## 95% CI : (0.86, 0.9543)
## No Information Rate : 0.8766
## P-Value [Acc > NIR] : 0.0840
##
## Kappa : 0.6345
## Mcnemar's Test P-Value : 0.5791
##
## Sensitivity : 0.73684
## Specificity : 0.94074
## Pos Pred Value : 0.63636
## Neg Pred Value : 0.96212
## Prevalence : 0.12338
## Detection Rate : 0.09091
## Detection Prevalence : 0.14286
## Balanced Accuracy : 0.83879
##
## 'Positive' Class : (-10,0]
##
## Variable S20.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 10 15
## (0,50] 9 118
##
## Accuracy : 0.8421
## 95% CI : (0.7742, 0.8961)
## No Information Rate : 0.875
## P-Value [Acc > NIR] : 0.9080
##
## Kappa : 0.3642
## Mcnemar's Test P-Value : 0.3074
##
## Sensitivity : 0.52632
## Specificity : 0.88722
## Pos Pred Value : 0.40000
## Neg Pred Value : 0.92913
## Prevalence : 0.12500
## Detection Rate : 0.06579
## Detection Prevalence : 0.16447
## Balanced Accuracy : 0.70677
##
## 'Positive' Class : (-10,0]
##
## Variable S2.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 12 33
## (0,50] 3 89
##
## Accuracy : 0.7372
## 95% CI : (0.6552, 0.8087)
## No Information Rate : 0.8905
## P-Value [Acc > NIR] : 1
##
## Kappa : 0.2821
## Mcnemar's Test P-Value : 1.343e-06
##
## Sensitivity : 0.80000
## Specificity : 0.72951
## Pos Pred Value : 0.26667
## Neg Pred Value : 0.96739
## Prevalence : 0.10949
## Detection Rate : 0.08759
## Detection Prevalence : 0.32847
## Balanced Accuracy : 0.76475
##
## 'Positive' Class : (-10,0]
##
## Variable S3.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 15 17
## (0,50] 1 121
##
## Accuracy : 0.8831
## 95% CI : (0.8216, 0.9292)
## No Information Rate : 0.8961
## P-Value [Acc > NIR] : 0.751747
##
## Kappa : 0.5647
## Mcnemar's Test P-Value : 0.000407
##
## Sensitivity : 0.9375
## Specificity : 0.8768
## Pos Pred Value : 0.4688
## Neg Pred Value : 0.9918
## Prevalence : 0.1039
## Detection Rate : 0.0974
## Detection Prevalence : 0.2078
## Balanced Accuracy : 0.9072
##
## 'Positive' Class : (-10,0]
##
## Variable S4.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 12 18
## (0,50] 5 113
##
## Accuracy : 0.8446
## 95% CI : (0.776, 0.8989)
## No Information Rate : 0.8851
## P-Value [Acc > NIR] : 0.94807
##
## Kappa : 0.4265
## Mcnemar's Test P-Value : 0.01234
##
## Sensitivity : 0.70588
## Specificity : 0.86260
## Pos Pred Value : 0.40000
## Neg Pred Value : 0.95763
## Prevalence : 0.11486
## Detection Rate : 0.08108
## Detection Prevalence : 0.20270
## Balanced Accuracy : 0.78424
##
## 'Positive' Class : (-10,0]
##
## Variable S5.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 9 4
## (0,50] 11 130
##
## Accuracy : 0.9026
## 95% CI : (0.8444, 0.9445)
## No Information Rate : 0.8701
## P-Value [Acc > NIR] : 0.1388
##
## Kappa : 0.4936
## Mcnemar's Test P-Value : 0.1213
##
## Sensitivity : 0.45000
## Specificity : 0.97015
## Pos Pred Value : 0.69231
## Neg Pred Value : 0.92199
## Prevalence : 0.12987
## Detection Rate : 0.05844
## Detection Prevalence : 0.08442
## Balanced Accuracy : 0.71007
##
## 'Positive' Class : (-10,0]
##
## Variable S6.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 11 27
## (0,50] 6 108
##
## Accuracy : 0.7829
## 95% CI : (0.7088, 0.8456)
## No Information Rate : 0.8882
## P-Value [Acc > NIR] : 0.9999392
##
## Kappa : 0.2903
## Mcnemar's Test P-Value : 0.0004985
##
## Sensitivity : 0.64706
## Specificity : 0.80000
## Pos Pred Value : 0.28947
## Neg Pred Value : 0.94737
## Prevalence : 0.11184
## Detection Rate : 0.07237
## Detection Prevalence : 0.25000
## Balanced Accuracy : 0.72353
##
## 'Positive' Class : (-10,0]
##
## Variable S7.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 8 6
## (0,50] 13 127
##
## Accuracy : 0.8766
## 95% CI : (0.8141, 0.9241)
## No Information Rate : 0.8636
## P-Value [Acc > NIR] : 0.3719
##
## Kappa : 0.3907
## Mcnemar's Test P-Value : 0.1687
##
## Sensitivity : 0.38095
## Specificity : 0.95489
## Pos Pred Value : 0.57143
## Neg Pred Value : 0.90714
## Prevalence : 0.13636
## Detection Rate : 0.05195
## Detection Prevalence : 0.09091
## Balanced Accuracy : 0.66792
##
## 'Positive' Class : (-10,0]
##
## Variable S8.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 11 38
## (0,50] 7 90
##
## Accuracy : 0.6918
## 95% CI : (0.6101, 0.7655)
## No Information Rate : 0.8767
## P-Value [Acc > NIR] : 1
##
## Kappa : 0.1806
## Mcnemar's Test P-Value : 7.744e-06
##
## Sensitivity : 0.61111
## Specificity : 0.70312
## Pos Pred Value : 0.22449
## Neg Pred Value : 0.92784
## Prevalence : 0.12329
## Detection Rate : 0.07534
## Detection Prevalence : 0.33562
## Balanced Accuracy : 0.65712
##
## 'Positive' Class : (-10,0]
##
## Variable S9.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,0] (0,50]
## (-10,0] 13 34
## (0,50] 4 88
##
## Accuracy : 0.7266
## 95% CI : (0.6446, 0.7987)
## No Information Rate : 0.8777
## P-Value [Acc > NIR] : 1
##
## Kappa : 0.2762
## Mcnemar's Test P-Value : 2.546e-06
##
## Sensitivity : 0.76471
## Specificity : 0.72131
## Pos Pred Value : 0.27660
## Neg Pred Value : 0.95652
## Prevalence : 0.12230
## Detection Rate : 0.09353
## Detection Prevalence : 0.33813
## Balanced Accuracy : 0.74301
##
## 'Positive' Class : (-10,0]
## Evaluación de predicción en rangos de temperaturas
conf_matrix_temp = conf_matrix(fitted,pred_sensores,test.set, my.breaks)## Variable S10.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 6 2 1 5 4
## (-5,0] 0 5 3 6 15 3
## (0,2] 1 3 4 2 2 3
## (2,5] 0 2 2 1 2 9
## (5,10] 0 1 4 5 14 11
## (10,50] 0 1 0 1 13 20
##
## Overall Statistics
##
## Accuracy : 0.2914
## 95% CI : (0.2204, 0.3708)
## No Information Rate : 0.3377
## P-Value [Acc > NIR] : 0.9027845
##
## Kappa : 0.1118
## Mcnemar's Test P-Value : 0.0001518
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.27778 0.26667
## Specificity 0.880000 0.79699 0.91912
## Pos Pred Value 0.000000 0.15625 0.26667
## Neg Pred Value 0.992481 0.89076 0.91912
## Prevalence 0.006623 0.11921 0.09934
## Detection Rate 0.000000 0.03311 0.02649
## Detection Prevalence 0.119205 0.21192 0.09934
## Balanced Accuracy 0.440000 0.53739 0.59289
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.062500 0.27451 0.4000
## Specificity 0.888889 0.79000 0.8515
## Pos Pred Value 0.062500 0.40000 0.5714
## Neg Pred Value 0.888889 0.68103 0.7414
## Prevalence 0.105960 0.33775 0.3311
## Detection Rate 0.006623 0.09272 0.1325
## Detection Prevalence 0.105960 0.23179 0.2318
## Balanced Accuracy 0.475694 0.53225 0.6257
## Variable S11.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 3 3 3 4 6
## (-5,0] 0 9 1 4 7 10
## (0,2] 0 4 5 3 6 3
## (2,5] 0 0 4 4 8 3
## (5,10] 0 1 1 1 10 7
## (10,50] 0 1 0 0 13 18
##
## Overall Statistics
##
## Accuracy : 0.3239
## 95% CI : (0.2479, 0.4075)
## No Information Rate : 0.338
## P-Value [Acc > NIR] : 0.6684
##
## Kappa : 0.177
## Mcnemar's Test P-Value : 3.037e-06
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.50000 0.35714
## Specificity 0.8662 0.82258 0.87500
## Pos Pred Value NA 0.29032 0.23810
## Neg Pred Value NA 0.91892 0.92562
## Prevalence 0.0000 0.12676 0.09859
## Detection Rate 0.0000 0.06338 0.03521
## Detection Prevalence 0.1338 0.21831 0.14789
## Balanced Accuracy NA 0.66129 0.61607
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.26667 0.20833 0.3830
## Specificity 0.88189 0.89362 0.8526
## Pos Pred Value 0.21053 0.50000 0.5625
## Neg Pred Value 0.91057 0.68852 0.7364
## Prevalence 0.10563 0.33803 0.3310
## Detection Rate 0.02817 0.07042 0.1268
## Detection Prevalence 0.13380 0.14085 0.2254
## Balanced Accuracy 0.57428 0.55098 0.6178
## Variable S12.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 7 1 1 2 0
## (-5,0] 0 8 6 5 7 1
## (0,2] 0 3 3 4 9 5
## (2,5] 0 1 2 4 11 6
## (5,10] 0 0 4 1 17 20
## (10,50] 0 0 0 0 4 22
##
## Overall Statistics
##
## Accuracy : 0.3506
## 95% CI : (0.2756, 0.4316)
## No Information Rate : 0.3506
## P-Value [Acc > NIR] : 0.5303
##
## Kappa : 0.1875
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.42105 0.18750
## Specificity 0.92857 0.85926 0.84783
## Pos Pred Value NA 0.29630 0.12500
## Neg Pred Value NA 0.91339 0.90000
## Prevalence 0.00000 0.12338 0.10390
## Detection Rate 0.00000 0.05195 0.01948
## Detection Prevalence 0.07143 0.17532 0.15584
## Balanced Accuracy NA 0.64016 0.51766
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.26667 0.3400 0.4074
## Specificity 0.85612 0.7596 0.9600
## Pos Pred Value 0.16667 0.4048 0.8462
## Neg Pred Value 0.91538 0.7054 0.7500
## Prevalence 0.09740 0.3247 0.3506
## Detection Rate 0.02597 0.1104 0.1429
## Detection Prevalence 0.15584 0.2727 0.1688
## Balanced Accuracy 0.56139 0.5498 0.6837
## Variable S13.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 1 0 7 5 10
## (-5,0] 0 4 5 4 17 7
## (0,2] 0 3 1 0 2 6
## (2,5] 0 4 4 0 7 4
## (5,10] 0 0 1 1 5 12
## (10,50] 0 1 0 2 3 12
##
## Overall Statistics
##
## Accuracy : 0.1719
## 95% CI : (0.111, 0.2486)
## No Information Rate : 0.3984
## P-Value [Acc > NIR] : 1
##
## Kappa : 0.0201
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.30769 0.090909
## Specificity 0.8203 0.71304 0.905983
## Pos Pred Value NA 0.10811 0.083333
## Neg Pred Value NA 0.90110 0.913793
## Prevalence 0.0000 0.10156 0.085938
## Detection Rate 0.0000 0.03125 0.007812
## Detection Prevalence 0.1797 0.28906 0.093750
## Balanced Accuracy NA 0.51037 0.498446
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.0000 0.12821 0.23529
## Specificity 0.8333 0.84270 0.92208
## Pos Pred Value 0.0000 0.26316 0.66667
## Neg Pred Value 0.8716 0.68807 0.64545
## Prevalence 0.1094 0.30469 0.39844
## Detection Rate 0.0000 0.03906 0.09375
## Detection Prevalence 0.1484 0.14844 0.14062
## Balanced Accuracy 0.4167 0.48545 0.57869
## Variable S14.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 3 1 0 1 0
## (-5,0] 0 10 5 5 3 0
## (0,2] 1 2 3 2 6 2
## (2,5] 0 3 2 5 7 0
## (5,10] 0 0 3 4 13 12
## (10,50] 0 0 1 0 20 40
##
## Overall Statistics
##
## Accuracy : 0.461
## 95% CI : (0.3805, 0.5431)
## No Information Rate : 0.3506
## P-Value [Acc > NIR] : 0.003054
##
## Kappa : 0.2856
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.55556 0.20000
## Specificity 0.967320 0.90441 0.90647
## Pos Pred Value 0.000000 0.43478 0.18750
## Neg Pred Value 0.993289 0.93893 0.91304
## Prevalence 0.006494 0.11688 0.09740
## Detection Rate 0.000000 0.06494 0.01948
## Detection Prevalence 0.032468 0.14935 0.10390
## Balanced Accuracy 0.483660 0.72998 0.55324
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.31250 0.26000 0.7407
## Specificity 0.91304 0.81731 0.7900
## Pos Pred Value 0.29412 0.40625 0.6557
## Neg Pred Value 0.91971 0.69672 0.8495
## Prevalence 0.10390 0.32468 0.3506
## Detection Rate 0.03247 0.08442 0.2597
## Detection Prevalence 0.11039 0.20779 0.3961
## Balanced Accuracy 0.61277 0.53865 0.7654
## Variable S15.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 3 3 4 9 5
## (-5,0] 0 5 2 4 12 6
## (0,2] 0 2 3 2 3 4
## (2,5] 0 1 0 4 5 4
## (5,10] 0 1 4 1 5 12
## (10,50] 0 0 0 1 5 14
##
## Overall Statistics
##
## Accuracy : 0.25
## 95% CI : (0.1766, 0.3357)
## No Information Rate : 0.3629
## P-Value [Acc > NIR] : 0.9973
##
## Kappa : 0.1018
## Mcnemar's Test P-Value : 2.085e-06
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.41667 0.25000
## Specificity 0.8065 0.78571 0.90179
## Pos Pred Value NA 0.17241 0.21429
## Neg Pred Value NA 0.92632 0.91818
## Prevalence 0.0000 0.09677 0.09677
## Detection Rate 0.0000 0.04032 0.02419
## Detection Prevalence 0.1935 0.23387 0.11290
## Balanced Accuracy NA 0.60119 0.57589
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.25000 0.12821 0.3111
## Specificity 0.90741 0.78824 0.9241
## Pos Pred Value 0.28571 0.21739 0.7000
## Neg Pred Value 0.89091 0.66337 0.7019
## Prevalence 0.12903 0.31452 0.3629
## Detection Rate 0.03226 0.04032 0.1129
## Detection Prevalence 0.11290 0.18548 0.1613
## Balanced Accuracy 0.57870 0.45822 0.6176
## Variable S16.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 3 2 2 3 5
## (-5,0] 0 4 3 5 8 8
## (0,2] 0 1 0 1 5 7
## (2,5] 0 1 2 2 5 3
## (5,10] 0 1 1 6 11 8
## (10,50] 0 0 3 1 7 25
##
## Overall Statistics
##
## Accuracy : 0.3158
## 95% CI : (0.238, 0.402)
## No Information Rate : 0.4211
## P-Value [Acc > NIR] : 0.9950946
##
## Kappa : 0.1333
## Mcnemar's Test P-Value : 0.0009435
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.40000 0.00000
## Specificity 0.8872 0.80488 0.88525
## Pos Pred Value NA 0.14286 0.00000
## Neg Pred Value NA 0.94286 0.90756
## Prevalence 0.0000 0.07519 0.08271
## Detection Rate 0.0000 0.03008 0.00000
## Detection Prevalence 0.1128 0.21053 0.10526
## Balanced Accuracy NA 0.60244 0.44262
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.11765 0.28205 0.4464
## Specificity 0.90517 0.82979 0.8571
## Pos Pred Value 0.15385 0.40741 0.6944
## Neg Pred Value 0.87500 0.73585 0.6804
## Prevalence 0.12782 0.29323 0.4211
## Detection Rate 0.01504 0.08271 0.1880
## Detection Prevalence 0.09774 0.20301 0.2707
## Balanced Accuracy 0.51141 0.55592 0.6518
## Variable S18.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 7 2 0 1 0
## (0,2] 0 8 5 3 2 0
## (2,5] 0 4 5 8 6 1
## (5,10] 0 0 4 5 20 11
## (10,50] 0 0 0 0 21 41
##
## Overall Statistics
##
## Accuracy : 0.526
## 95% CI : (0.444, 0.6069)
## No Information Rate : 0.3442
## P-Value [Acc > NIR] : 2.791e-06
##
## Kappa : 0.3601
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.36842 0.31250
## Specificity 1 0.97778 0.90580
## Pos Pred Value NA 0.70000 0.27778
## Neg Pred Value NA 0.91667 0.91912
## Prevalence 0 0.12338 0.10390
## Detection Rate 0 0.04545 0.03247
## Detection Prevalence 0 0.06494 0.11688
## Balanced Accuracy NA 0.67310 0.60915
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.50000 0.4000 0.7736
## Specificity 0.88406 0.8077 0.7921
## Pos Pred Value 0.33333 0.5000 0.6613
## Neg Pred Value 0.93846 0.7368 0.8696
## Prevalence 0.10390 0.3247 0.3442
## Detection Rate 0.05195 0.1299 0.2662
## Detection Prevalence 0.15584 0.2597 0.4026
## Balanced Accuracy 0.69203 0.6038 0.7828
## Variable S19.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 0 0 0 0 0
## (-5,0] 0 12 5 1 2 0
## (0,2] 0 5 6 4 4 0
## (2,5] 0 2 2 8 14 3
## (5,10] 0 0 2 3 20 17
## (10,50] 0 0 0 0 9 35
##
## Overall Statistics
##
## Accuracy : 0.526
## 95% CI : (0.444, 0.6069)
## No Information Rate : 0.3571
## P-Value [Acc > NIR] : 1.367e-05
##
## Kappa : 0.3792
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.63158 0.40000
## Specificity 1 0.94074 0.90647
## Pos Pred Value NA 0.60000 0.31579
## Neg Pred Value NA 0.94776 0.93333
## Prevalence 0 0.12338 0.09740
## Detection Rate 0 0.07792 0.03896
## Detection Prevalence 0 0.12987 0.12338
## Balanced Accuracy NA 0.78616 0.65324
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.50000 0.4082 0.6364
## Specificity 0.84783 0.7905 0.9091
## Pos Pred Value 0.27586 0.4762 0.7955
## Neg Pred Value 0.93600 0.7411 0.8182
## Prevalence 0.10390 0.3182 0.3571
## Detection Rate 0.05195 0.1299 0.2273
## Detection Prevalence 0.18831 0.2727 0.2857
## Balanced Accuracy 0.67391 0.5993 0.7727
## Variable S1.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 1 0 0 0 0
## (-5,0] 0 13 5 3 0 0
## (0,2] 0 4 4 4 4 1
## (2,5] 0 0 3 7 9 2
## (5,10] 0 1 4 3 24 12
## (10,50] 0 0 0 0 10 40
##
## Overall Statistics
##
## Accuracy : 0.5714
## 95% CI : (0.4893, 0.6508)
## No Information Rate : 0.3571
## P-Value [Acc > NIR] : 4.976e-08
##
## Kappa : 0.4312
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.68421 0.25000
## Specificity 0.993506 0.94074 0.90580
## Pos Pred Value NA 0.61905 0.23529
## Neg Pred Value NA 0.95489 0.91241
## Prevalence 0.000000 0.12338 0.10390
## Detection Rate 0.000000 0.08442 0.02597
## Detection Prevalence 0.006494 0.13636 0.11039
## Balanced Accuracy NA 0.81248 0.57790
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.41176 0.5106 0.7273
## Specificity 0.89781 0.8131 0.8990
## Pos Pred Value 0.33333 0.5455 0.8000
## Neg Pred Value 0.92481 0.7909 0.8558
## Prevalence 0.11039 0.3052 0.3571
## Detection Rate 0.04545 0.1558 0.2597
## Detection Prevalence 0.13636 0.2857 0.3247
## Balanced Accuracy 0.65479 0.6619 0.8131
## Variable S20.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 2 2 0 1 0
## (-5,0] 0 8 4 3 4 1
## (0,2] 0 1 2 4 3 0
## (2,5] 0 5 2 3 7 3
## (5,10] 1 2 2 2 17 17
## (10,50] 0 0 3 3 13 37
##
## Overall Statistics
##
## Accuracy : 0.4408
## 95% CI : (0.3604, 0.5235)
## No Information Rate : 0.3816
## P-Value [Acc > NIR] : 0.07875
##
## Kappa : 0.2487
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.44444 0.13333
## Specificity 0.966887 0.91045 0.94161
## Pos Pred Value 0.000000 0.40000 0.20000
## Neg Pred Value 0.993197 0.92424 0.90845
## Prevalence 0.006579 0.11842 0.09868
## Detection Rate 0.000000 0.05263 0.01316
## Detection Prevalence 0.032895 0.13158 0.06579
## Balanced Accuracy 0.483444 0.67745 0.53747
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.20000 0.3778 0.6379
## Specificity 0.87591 0.7757 0.7979
## Pos Pred Value 0.15000 0.4146 0.6607
## Neg Pred Value 0.90909 0.7477 0.7813
## Prevalence 0.09868 0.2961 0.3816
## Detection Rate 0.01974 0.1118 0.2434
## Detection Prevalence 0.13158 0.2697 0.3684
## Balanced Accuracy 0.53796 0.5767 0.7179
## Variable S2.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 6 2 4 2 3
## (-5,0] 0 6 2 2 10 8
## (0,2] 0 1 2 5 5 9
## (2,5] 0 1 1 2 5 1
## (5,10] 0 1 4 1 12 11
## (10,50] 0 0 1 2 12 16
##
## Overall Statistics
##
## Accuracy : 0.2774
## 95% CI : (0.2043, 0.3603)
## No Information Rate : 0.3504
## P-Value [Acc > NIR] : 0.9718
##
## Kappa : 0.102
## Mcnemar's Test P-Value : 6.988e-05
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.4000 0.16667
## Specificity 0.8759 0.8197 0.84000
## Pos Pred Value NA 0.2143 0.09091
## Neg Pred Value NA 0.9174 0.91304
## Prevalence 0.0000 0.1095 0.08759
## Detection Rate 0.0000 0.0438 0.01460
## Detection Prevalence 0.1241 0.2044 0.16058
## Balanced Accuracy NA 0.6098 0.50333
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.12500 0.26087 0.3333
## Specificity 0.93388 0.81319 0.8315
## Pos Pred Value 0.20000 0.41379 0.5161
## Neg Pred Value 0.88976 0.68519 0.6981
## Prevalence 0.11679 0.33577 0.3504
## Detection Rate 0.01460 0.08759 0.1168
## Detection Prevalence 0.07299 0.21168 0.2263
## Balanced Accuracy 0.52944 0.53703 0.5824
## Variable S3.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 3 0 0 0 0
## (-5,0] 0 12 7 5 5 0
## (0,2] 0 1 7 3 3 5
## (2,5] 0 0 2 8 16 8
## (5,10] 0 0 3 0 14 23
## (10,50] 0 0 0 0 3 26
##
## Overall Statistics
##
## Accuracy : 0.4351
## 95% CI : (0.3555, 0.5172)
## No Information Rate : 0.4026
## P-Value [Acc > NIR] : 0.2291
##
## Kappa : 0.2914
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.75000 0.36842
## Specificity 0.98052 0.87681 0.91111
## Pos Pred Value NA 0.41379 0.36842
## Neg Pred Value NA 0.96800 0.91111
## Prevalence 0.00000 0.10390 0.12338
## Detection Rate 0.00000 0.07792 0.04545
## Detection Prevalence 0.01948 0.18831 0.12338
## Balanced Accuracy NA 0.81341 0.63977
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.50000 0.34146 0.4194
## Specificity 0.81159 0.76991 0.9674
## Pos Pred Value 0.23529 0.35000 0.8966
## Neg Pred Value 0.93333 0.76316 0.7120
## Prevalence 0.10390 0.26623 0.4026
## Detection Rate 0.05195 0.09091 0.1688
## Detection Prevalence 0.22078 0.25974 0.1883
## Balanced Accuracy 0.65580 0.55569 0.6934
## Variable S4.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 5 4 1 0 0
## (-5,0] 0 7 2 1 8 2
## (0,2] 0 1 2 3 1 0
## (2,5] 0 0 1 2 9 4
## (5,10] 0 3 3 6 10 10
## (10,50] 0 1 4 2 19 37
##
## Overall Statistics
##
## Accuracy : 0.3919
## 95% CI : (0.3128, 0.4754)
## No Information Rate : 0.3581
## P-Value [Acc > NIR] : 0.2193
##
## Kappa : 0.1863
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.4118 0.12500
## Specificity 0.93243 0.9008 0.96212
## Pos Pred Value NA 0.3500 0.28571
## Neg Pred Value NA 0.9219 0.90071
## Prevalence 0.00000 0.1149 0.10811
## Detection Rate 0.00000 0.0473 0.01351
## Detection Prevalence 0.06757 0.1351 0.04730
## Balanced Accuracy NA 0.6563 0.54356
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.13333 0.21277 0.6981
## Specificity 0.89474 0.78218 0.7263
## Pos Pred Value 0.12500 0.31250 0.5873
## Neg Pred Value 0.90152 0.68103 0.8118
## Prevalence 0.10135 0.31757 0.3581
## Detection Rate 0.01351 0.06757 0.2500
## Detection Prevalence 0.10811 0.21622 0.4257
## Balanced Accuracy 0.51404 0.49747 0.7122
## Variable S5.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 1 0 0 0 0
## (-5,0] 1 7 3 1 0 0
## (0,2] 0 5 3 2 2 0
## (2,5] 0 5 6 7 12 2
## (5,10] 0 1 2 5 19 16
## (10,50] 0 0 1 0 14 39
##
## Overall Statistics
##
## Accuracy : 0.487
## 95% CI : (0.4058, 0.5688)
## No Information Rate : 0.3701
## P-Value [Acc > NIR] : 0.00199
##
## Kappa : 0.3137
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.36842 0.20000
## Specificity 0.993464 0.96296 0.93525
## Pos Pred Value 0.000000 0.58333 0.25000
## Neg Pred Value 0.993464 0.91549 0.91549
## Prevalence 0.006494 0.12338 0.09740
## Detection Rate 0.000000 0.04545 0.01948
## Detection Prevalence 0.006494 0.07792 0.07792
## Balanced Accuracy 0.496732 0.66569 0.56763
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.46667 0.4043 0.6842
## Specificity 0.82014 0.7757 0.8454
## Pos Pred Value 0.21875 0.4419 0.7222
## Neg Pred Value 0.93443 0.7477 0.8200
## Prevalence 0.09740 0.3052 0.3701
## Detection Rate 0.04545 0.1234 0.2532
## Detection Prevalence 0.20779 0.2792 0.3506
## Balanced Accuracy 0.64341 0.5900 0.7648
## Variable S6.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 3 1 1 2 2
## (-5,0] 0 8 2 5 5 9
## (0,2] 0 2 3 2 5 5
## (2,5] 0 4 2 2 3 7
## (5,10] 0 0 5 4 16 15
## (10,50] 0 0 1 2 11 25
##
## Overall Statistics
##
## Accuracy : 0.3553
## 95% CI : (0.2794, 0.4369)
## No Information Rate : 0.4145
## P-Value [Acc > NIR] : 0.94207
##
## Kappa : 0.17
## Mcnemar's Test P-Value : 0.01465
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.47059 0.21429
## Specificity 0.94079 0.84444 0.89855
## Pos Pred Value NA 0.27586 0.17647
## Neg Pred Value NA 0.92683 0.91852
## Prevalence 0.00000 0.11184 0.09211
## Detection Rate 0.00000 0.05263 0.01974
## Detection Prevalence 0.05921 0.19079 0.11184
## Balanced Accuracy NA 0.65752 0.55642
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.12500 0.3810 0.3968
## Specificity 0.88235 0.7818 0.8427
## Pos Pred Value 0.11111 0.4000 0.6410
## Neg Pred Value 0.89552 0.7679 0.6637
## Prevalence 0.10526 0.2763 0.4145
## Detection Rate 0.01316 0.1053 0.1645
## Detection Prevalence 0.11842 0.2632 0.2566
## Balanced Accuracy 0.50368 0.5814 0.6198
## Variable S7.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 1 0 0 0 0
## (-5,0] 0 7 3 3 0 0
## (0,2] 1 9 4 4 5 0
## (2,5] 0 3 6 5 14 7
## (5,10] 0 0 1 5 24 27
## (10,50] 0 0 1 0 5 19
##
## Overall Statistics
##
## Accuracy : 0.3831
## 95% CI : (0.306, 0.4648)
## No Information Rate : 0.3442
## P-Value [Acc > NIR] : 0.1751
##
## Kappa : 0.2072
## Mcnemar's Test P-Value : NA
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.000000 0.35000 0.26667
## Specificity 0.993464 0.95522 0.86331
## Pos Pred Value 0.000000 0.53846 0.17391
## Neg Pred Value 0.993464 0.90780 0.91603
## Prevalence 0.006494 0.12987 0.09740
## Detection Rate 0.000000 0.04545 0.02597
## Detection Prevalence 0.006494 0.08442 0.14935
## Balanced Accuracy 0.496732 0.65261 0.56499
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.29412 0.5000 0.3585
## Specificity 0.78102 0.6887 0.9406
## Pos Pred Value 0.14286 0.4211 0.7600
## Neg Pred Value 0.89916 0.7526 0.7364
## Prevalence 0.11039 0.3117 0.3442
## Detection Rate 0.03247 0.1558 0.1234
## Detection Prevalence 0.22727 0.3701 0.1623
## Balanced Accuracy 0.53757 0.5943 0.6495
## Variable S8.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 3 1 1 9 5
## (-5,0] 0 8 2 5 10 5
## (0,2] 0 3 2 2 3 1
## (2,5] 0 3 0 4 7 3
## (5,10] 0 1 4 3 9 8
## (10,50] 0 0 2 2 10 30
##
## Overall Statistics
##
## Accuracy : 0.363
## 95% CI : (0.2851, 0.4466)
## No Information Rate : 0.3562
## P-Value [Acc > NIR] : 0.462312
##
## Kappa : 0.1955
## Mcnemar's Test P-Value : 0.001466
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity NA 0.44444 0.18182
## Specificity 0.8699 0.82812 0.93333
## Pos Pred Value NA 0.26667 0.18182
## Neg Pred Value NA 0.91379 0.93333
## Prevalence 0.0000 0.12329 0.07534
## Detection Rate 0.0000 0.05479 0.01370
## Detection Prevalence 0.1301 0.20548 0.07534
## Balanced Accuracy NA 0.63628 0.55758
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.2353 0.18750 0.5769
## Specificity 0.8992 0.83673 0.8511
## Pos Pred Value 0.2353 0.36000 0.6818
## Neg Pred Value 0.8992 0.67769 0.7843
## Prevalence 0.1164 0.32877 0.3562
## Detection Rate 0.0274 0.06164 0.2055
## Detection Prevalence 0.1164 0.17123 0.3014
## Balanced Accuracy 0.5673 0.51212 0.7140
## Variable S9.min_t
## Confusion Matrix and Statistics
##
## Reference
## Prediction (-10,-5] (-5,0] (0,2] (2,5] (5,10] (10,50]
## (-10,-5] 0 6 4 2 2 2
## (-5,0] 2 5 6 6 10 2
## (0,2] 0 0 0 3 6 1
## (2,5] 0 0 2 0 8 5
## (5,10] 0 3 1 3 6 8
## (10,50] 0 1 0 1 15 29
##
## Overall Statistics
##
## Accuracy : 0.2878
## 95% CI : (0.2142, 0.3706)
## No Information Rate : 0.3381
## P-Value [Acc > NIR] : 0.9120812
##
## Kappa : 0.1018
## Mcnemar's Test P-Value : 0.0004624
##
## Statistics by Class:
##
## Class: (-10,-5] Class: (-5,0] Class: (0,2]
## Sensitivity 0.00000 0.33333 0.00000
## Specificity 0.88321 0.79032 0.92063
## Pos Pred Value 0.00000 0.16129 0.00000
## Neg Pred Value 0.98374 0.90741 0.89922
## Prevalence 0.01439 0.10791 0.09353
## Detection Rate 0.00000 0.03597 0.00000
## Detection Prevalence 0.11511 0.22302 0.07194
## Balanced Accuracy 0.44161 0.56183 0.46032
## Class: (2,5] Class: (5,10] Class: (10,50]
## Sensitivity 0.0000 0.12766 0.6170
## Specificity 0.8790 0.83696 0.8152
## Pos Pred Value 0.0000 0.28571 0.6304
## Neg Pred Value 0.8790 0.65254 0.8065
## Prevalence 0.1079 0.33813 0.3381
## Detection Rate 0.0000 0.04317 0.2086
## Detection Prevalence 0.1079 0.15108 0.3309
## Balanced Accuracy 0.4395 0.48231 0.7161